Ho khetholla li-gamers tsa Inthanete tse sa sebetseng le tse sa sebeliseng maloetse ka ho sebelisa likarolo tse nyenyane tsa methapo ea pelo (2018)

. 2018; 9: 291.

E hatisitsoe Inthaneteng 2018 Jun 29. doi:  10.3389 / fpsyt.2018.00291

PMCID: PMC6033968

PMID: 30008681

inahaneloang

Bothata ba lipapali tsa inthanete (IGD) bo lula bo fumanoa boits'ebetsong ba melaoana e robong e tlasa mofuta oa morao-rao oa Diagnostic and Statistical Manual of Mental Dis shida (DSM-5). Mona, re ile ra hlahloba hore na likarolo tse joalo tsa matšoao li ka fetoleloa e le karohano e thehiloeng ho complication. Lintlha tsa Structural MRI (sMRI) le infusion-weight M MMA (dMRI) li fumanoe ho libapali tsa 38 tse fumanoeng li na le IGD, libapali tse tloaelehileng tsa 68 tse fumanoang li se na IGD, le 37 e se nang lipapali. Re hlahisitse likarolo tsa 108 tsa sebopeho sa bohlooho (GM) le sebopeho se tšoeu (WM) ho tsoa data ea MRI. Ha ho hlophisoa khafetsa ho laoloang ka thepa ho sebelisoa likarolo tsa 108 neuroanatomical ho khetha tse bohlokoa bakeng sa karohano lipakeng tsa lihlopha, libapali tse sa tsotelleng le tse tloaelehileng li ne li emeloa ho latela likarolo tsa 43 le 21, ka ho latellana, mabapi le bao e seng libapali tse phetseng hantle, athe Bapalami ba sa tsotelleng ba ile ba emeloa ho latela likarolo tsa 11 mabapi le libapali tse tloaelehileng. Mechining ea veter ea ts'ehetso (SVM) e sebelisang likarolo tse bobebe tsa morao-rao joaloka batsoalisi, libapali tse sa tsotelleng le tse tloaelehileng li ile tsa khetholloa ka katleho, ka ho nepahala ho feta 98%, ho tsoa ho bao e neng e se libapali tse phetseng hantle, empa karohano lipakeng tsa libapali tse sa tsotelleng le tse tloaelehileng e ne e le phephetso. Liphumano tsena li fana ka maikutlo a hore libapali tsa methapo ea kutlo le tseo e seng tsa methapo ea kutlo joalo ka karolo ea DSM-5 li ka emeloa ke likarolo tsa sparse neuroanatomical, haholoholo maemong a ho khetholla batho ba sa pheleng hantle.

Keywords: bothata ba papali ea marang-rang, tlhahlobo ea tlhahlobo ea mafu, MRI ea sebopeho, MRI e nang le boima ba 'mele, regression e tloaelehileng

Selelekela

Leha e le ho khothaletsoa e le temallo ea methapo ea kutlo bakeng sa mashome a lilemo (), haufinyane tjena ho sa tsoa bea letoto la lipapali tsa marang-rang (IGD) ho Diagnostic and Statistical Manual of Mental Dis shida (DSM). Khatiso ea bohlano ea DSM (DSM-5) () e thathamisitse IGD e le boemo ba ho tsoela pele ho ithuta le ho fana ka mekhoa e robong ea ho e fumana. Ka tatellano e thehiloeng ka matšoao ho sebelisa lenane la lintlha tse robong tsa IGD (IGDS) e reriloeng ho DSM − 5, monyako oa ho ba le mekhoa e mehlano kapa ho feta o ile oa sebelisoa ho fumanoeng tlhahlobo ea IGD. Le ha sebaka sena se fokotsoang se ka bapisa libapali tsa 'mele ka ho lekaneng tse nang le mathata a tebileng a ho senyeha (), mofuta oa dichotomous oa lintho tsa IGDS ka mokhoa o hlakileng o kenyelletsa tlhahlobo e kholo ea ho hlahloba kapa ho hlaka.

Ntle le matšoao, mefuta e mengata ea dysfunctions tse amanang le IGD hangata e bonoa, liphetoho tse fokolang tsa neuroanatomical. Ho joalo, mosebetsi o moholo o bonts'itse hore IGD e amahanngoa le liphetoho tsa sebopeho bokong: shrinkage of grey factor (GM) volume (-), phokotso ea boima ba cortical (), le tahlehelo ea botshepehi ba litaba tse tšoeu (WM) (, ) li bontšitsoe ka mokhoa o tloaelehileng. Liphetoho tsena tsa neuroanatomical tse amanang le IGD li fana ka maikutlo a hore likarolo tse joalo tsa monahano oa kelello li ka sebetsa e le li-biomarkers ho khetholla batho ba nang le IGD ho batho ba bang. Ka mantsoe a mang, tlhahlobo ea IGD e kanna ea etsoa ka ho qhekella ka li-biomarkers tsa neuroanatomical, ho fapana le ho khetholla matšoao a thehiloeng ho DSM-5. Liteko tsena li kanna tsa tsamaellana le boiteko ba ho fetela tlhatlhobo e hlalosang ka ho sebelisa mekhoa e amanang le tlhoko ea kelello (), ka ho khetheha mekhoa e tsamaisoang ke data e mabapi le ho ithuta ka mochini (ML) ho sebetsana le tlhahlobo ea mafu a kelello ().

Phuputsong ena, re batlile khokahano lipakeng tsa tatellano e thehiloeng matšoao motheong oa IGDS le tlhaiso-lipakeng ea complication ka ho sebelisa li-biomarkers tsa neuroanatomical tlhahlobo ea IGD. Hobane likarolo tse ling tsa GM le WM tsa boko li ka khona ho kenyelletsa tlhaiso-leseling kapa tlhaiso-leseling e sa sebetseng bakeng sa tlhahlobo ea tlhahlobo ea mafu, re batlile ho khetha likarolo tsa sparse neuroanatomical ka ho sebelisa regression e tloaelehileng. Re fane ka maikutlo a hore karohano e thehiloeng matšoao e ka emeloa ho latela likarolo tse fokolang tsa neuroanatomical tse tla etsa mefuta e khetholloang bakeng sa tlhahlobo ea IGD. Libapali tsa boloetse ba lipilisi tse fumanoeng li na le IGD ho ne ho nahanoa hore li fapana le batho ba sa pheleng hantle ho feta ho libapali tse fumanoang li se na IGD, ke hore, libapali tse seng tsa 'mele. ka hona, libapali tsa li-pathological li ka tšoauoa ka palo e kholo ea likarolo ha li bapisoa le libapali tse seng tsa methapo mabapi le libapali tse sa pheleng hantle. Ntle le moo, re ne re batla ho etsa qeto ea hore na libapali tse sa pheleng li ka khetholoha ho libapali tsa methapo kapa ho batho ba sa pheleng ba lipapali. Batho ba sa bapalang papali eo e seng ea 'mele ba ka nkoa e le batho ba haufi le batho ba sa pheleng hantle ho latela matšoao a hlalosang, empa re ne re nahana hore mohopolo o joalo o hloka ho netefatsoa ka ho hlophisoa ka sepheo sa complication.

Lisebelisoa le mekhoa

barupeluoa ba

Har'a barupeluoa ba 237 ba bapalang lipapali tse thehiloeng ho Marang-rang, batho ba 106 ba khethiloe ntle le bao ba bonts'itseng phoso pakeng tsa IGDS e itlalehileng le puisano e hlophisitsoeng le setsebi sa kelello sa tlhahlobo ea tlhahlobo ea IGD kapa ba lahlehileng kapa ba sentse data ea monahano oa boko. Motheong oa IGDS, batho ba 38 (lilemo tsa 27.66 ± 5.61; basali ba 13) ba ileng ba khotsofatsa bonyane lintho tse hlano tsa IGDS ba ile ba ngoloa hore ke libapali tsa disordered le batho ba 68 (basali ba 27.96 ± 6.41; basali ba 21) ba khotsofalitseng boholo ba ntho e le 'ngoe ea IGDS libapali tse tloaelehileng. Batho ka bo mong ba khotsofalitseng lintho tsa IGDS lipakeng tsa tse peli ho isa ho tse 'ne ba boetse ba sa kenyelletsoe, hobane ba kanna ba khetholloa e le sehlopha se seng lipakeng tsa libapali tse sa tsotelleng le tse tloaelehileng (). Ntle le moo, batho ba 37 (lilemo tse 25.86 ± 4.10; basali ba 13) ba sa bapalang lipapali tse thehiloeng marang-rang ba ile ba thaothoa ka thoko, mme ba nkuoa e le libapali tse phetseng hantle. Ho ba sieo ha comorbidities ho bankakarolo bohle ho netefalitsoe. Tumello e ngotsoeng e nang le tsebo e fumanoe ho bankakarolo bohle ho latela Phatlalatso ea Helsinki le liphetoho tsa eona tsa morao-rao, mme thuto e ile ea ananeloa ke Boto ea Setsi sa Tlhahlobo ea Sepetlele sa Seoul St.

Tsebo ea data ea MRI

Lintlha tsa Structural MRI (sMRI) le data-boima ba MRI (dMRI) li ile tsa bokelloa ho sebelisoa sistimi ea 3 T MAGNETOM Verio (Nokia AG, Erlangen, Germany). Ho fumaneha ha data ea sMRI ho ile ha etsoa ho sebelisoa ka tatellano e hlophisitsoeng e potlakileng ea gradient: palo ea linthana ka sefofaneng sa sagittal = 176, bophara ba lesela = 1 mm, boholo ba matrix = 256 × 256, le qeto ea sefofaneng = 1 × 1 mm . Bakeng sa ho fumana data ea dMRI, ho kenyelletsa kh'outu ea gradient ho entsoe ka mekhoa ea 30 le b = 1,000 s / mm2 mme ho sebelisitsoe tatellano e le 'ngoe ea echo-planar imaging e le' ngoe: palo ea maseka ka sefofaneng sa axial = 75, botenya ba sekhahla = 2 mm, boholo ba matrix = 114 × 114, le qeto ea sefofane = 2 × 2 mm.

Ts'ebetso ea data ea MRI

Lisebelisoa tse kenyellelitsoeng ho CAT12 (http://www.neuro.uni-jena.de/cat/) li ne li sebelisetsoa ho sebetsana le datha ea sMRI. Setšoantšo sa bophahamo ba boko se ne se arotsoe ka likarolo tse fapaneng, ho kenyeletsoa GM, WM, le mokelikeli oa corticospinal le ho ngolisoa ka boqhetseke ho boko bo supang sebakeng se tloaelehileng. Bukeng ea voxel-based morphometry (VBM), bophahamo ba bohlale ba voxel bo ile ba hakangoa ka ho eketsa menyetla ea ho ba GM ka bophahamo ba voxel, mme litekanyetso tseo li ile tsa aroloa ka bongata ba intracranial bophahamo ba ho fetolela liphapang tsa motho ka mong. Ka sebopeho se thehiloeng morphometry (SBM), botebo ba cortical bo ne bo hakantsoe ho sebelisoa mokhoa oa ho lekanya o thehiloeng holima ().

Ts'ebetso ea data ea dMRI

Lisebelisoa tse kenyellelitsoeng ho FSL 5.0 (http://fsl.fmrib.ox.ac.uk/fsl/) ba ne ba hiriloe ho sebetsa litaba tsa dMRI. Litšoantšo tsohle li ile tsa fetisetsoa ho setšoantšo se setle se fumanoeng ka b = 0 s / mm2 ho lokisa liphoso tsa eddy tsa hona joale le motsamao oa hlooho. Ho ile ha qaptjoa methapo ea kutlo e fetisisang ho voxel e 'ngoe le e' ngoe kahare ho bokong, 'me matekanyetso a nkiloeng ka maqhubu a kenyelletsoeng, ho kenyeletsa le anisotropy (FA), a bolela phapang (MD), axial diffusivity (AD), le radial diffusivity (RD), tse kopantsoeng; fuoa li-diffusivity tse tharo tse fapaneng le tsepe e fapaneng ea tensor ea infusion, FA e ile ea baloa e le motso oa sekwere oa kakaretso ea libaka tse fapaneng pakeng tsa lilepe tse tharo, MD e le phapano e pakeng tsa maqhubu a mararo, AD joalo ka karohano e kholo ho feta axis e kholo , le RD joalo ka karolelano ea kusiyana pakeng tsa likhaba tse peli tse nyane. Re sebelisa lipalopalo tse amanang le sebaka se amanang le sebaka (TBSS) () e kentsoe tšebetsong ho FSL 5.0, 'mapa oa li-parameter tse hlahisoang ka mokhoa o thellisitsoeng o ile oa ngolisoa ka nqane ho bokong ba boitsebisong sebakeng se tloaelehileng,' me ba kenngoa mohlaleng oa skeleton ea WM.

Mokhahlelo

Mehato e 'meli e meholo ea ho rala mofuta oa khethollo ke karolo ea karolo le khetho. Re hlahisitse likarolo ho tsoa ho neuroanatomy, haholo-holo bophahamo le botenya ba likarolo tsa GM le ho tšepahala le ho fapana ha lipampitšana tsa WM. Kamora ho lekanya bophahamo ba GM le boholo ba cortical joalo ka limmapa tse bohlale tsa voxel tse fumanoeng ho VBM le SBM, ka ho latellana, litekanyetso li ile tsa hlahlojoa bakeng sa e 'ngoe le e' ngoe ea libaka tsa GM tsa 60 (Lethathamo S1), e ts'ehetsoeng joalo ka hofetisisa tsa Hammers (), joalo ka karolelano ea voxels tsohle tse ka ho eona. Kaha ho na le lipalo-palo tsa tekanyetso tse bakiloeng ke ho se sebetse hantle, ho kenyeletsa le FA, MD, AD, le RD joalo ka limmapa tse bohlale tsa voxel ho skeleton sa WM se fumanoeng ho TBSS, lipalamo li ne li kopantsoe bakeng sa lipampitšana tsohle tsa 48 WM (Lethathamo S2), e ts'ehetsoe joalo ka ho atlasetso ea ICBM DTI-81 (), joalo ka karolelano ea voxels tsohle tse ka ho eona. Ka kakaretso, re ile ra nahana ka likarolo tse peli tsa GM le li-parameter tse nne tsa WM, tse hlahisitseng li-parameter tse robeli tsa GM le WM. Bakeng sa motsoako o mong le o mong oa likarolo tsa GM le WM, boleng ba paramente ea libaka tsa 60 GM le lipampitšana tsa 48 WM li kentse kakaretso ea likarolo tsa 108 neuroanatomical.

Tlhopho ea litšobotsi ka khatello e tloaelehileng

Ho fokotsa palo ea likarolo ho bohlokoa, haholo-holo bakeng sa data e nang le palo e kholo ea likarolo le palo e lekantsoeng ea lipatlisiso. Palo e lekantsoeng ea lipalo mabapi le palo ea likarolo e ka lebisa ho fetelisang lerata, 'me ho etsa lintho khafetsa ke mokhoa o thusang ho fokotsa kapa ho thibela ho fetisa ka ho tlisa tlhaiso-leseling kapa likhatello holima mohlala. Hobane likarolo tsohle tsa 108 li kanna tsa se kenyele tlhaiso-leseling e hlokahalang le e hlokahalang bakeng sa ho khetholla, re khethile likarolo tsa sparse ka ho sebelisa regression e tloaelehileng. Ka ho khetheha, lasso (le net) e ne e sebelisoa bakeng sa ho hlophisa khafetsa ha thepa. Lasso e kenyelletsa polelo ea kotlo, kapa paramente ea ho hlophisoa, λ, e hatisang boholo ba likhakanyo tse phethahetseng mohlaleng oa ho beha thepa. Hobane keketseho ea λ e lebisa ho li-coefficients tse theko e phahameng ka ho fetisisa, lasso e fana ka mohlala o fokotsitsoeng oa ho boloka thepa le baphatlalatsi ba fokolang. Letlooa la elastic le hlahisa mofuta o fokolisitsoeng oa ho khutlisa molemong oa ho etsa li-coefficients ho zero, haholoholo ka ho kenyelletsa paramente ea hybrid e tloaelehileng ea lasso le ridge regression, e hlola thibelo ea lasso ho phekola li-Forecast tse lumellanang haholo ().

Bakeng sa karohano lipakeng tsa sehlopha ka seng sa lihlopha tsena tse tharo, re ile ra sebelisa lasso le elastic net ho khetholla li-Forecast tsa bohlokoa nakong ea likarolo tsa 108 neuroanatomic ka mokhoa oa ho ngola. Likarolo tsa 108 tsa batho bohle sehlopheng ka seng sa lihlopha tsena tse tharo li ne li lekantsoe ho etsa matrix ea datha, A, moo mola o mong le o mong o neng o emela pono e le 'ngoe' me kholomo ka 'ngoe e emela sebui se le seng. Ho lokisa litlamorao tsa lilemo tsa batho ka bong le thobalano ho li-parameter tsa GM le WM, matrix a setseng, R, e hlahisitsoe: R = I-C(CTC)-1C moo I e ne e le lengolo la boitsebiso le C e ne e le matrix a coding e ferekanyang li-covariates tsa lilemo le thobalano. E ile ea sebelisoa ho A ho fumana libaka tsa bolulo kamora ho ngolisa li-covariate tse ferekanyang: X = RA.

Fuoa matrix ea data e fetotsoeng, X, le karabelo, Y, e nang le lihlopha tse peli tsa batho, 10-fold cross-neteation (CV) e sebelisitsoe ho batla paramente e sebetsang.MinErr, e faneng ka phoso e nyane ka ho fetisisa mabapi le ho kheloha, ho hlalosoa e le monyetla o mong o sa nepahalang oa ho etsa mohlala oa tlhahlobo e lekantsoeng holim'a mealo ea netefatso. Ntle le moo, hobane CV e na le liphoso ho e mong le e mong ea hlahloboang, paramente e tloaelehileng1SE, e fumanoeng kahare ho phoso e le 'ngoe ea phoso e fokolang ea CV ntlheng ea ho eketsa tloaelo ho tsoa ho λMinErr le eona e ile ea nkuoa. Ka mantsoe a mang, likarolo tsa sparser li ile tsa khethoa ho λ1SE, athe likarolo tsa sparse li ne li ikemiselitsoe ho λMinErr. Ts'ebetso ena ea ho batla mokhoa o hlophisitsoeng oa ho khutlisa oa thepa o nang le likhakanyo tse nyane o ile oa phetoa molemong o mong le o mong oa likarolo tsa GM le WM tse nang le likarolo tsa 108 neuroanatomical.

Ts'ebetso ea likarolo tse khethiloeng

Ho lekola molemo oa likarolo tsa sparse le sparser, ts'ebetso e ile ea bapisoa pakeng tsa mohlala le likarolo tse fokolitsoeng tsa palo le mohlala ka likarolo tsohle tsa 108 mochini oa tšeetso (veV) ka ho lekanya moamoheli ea sebetsang (ROC) curve. Ka kernel ea mola e le ts'ebetso ea kernel le li-hyperparameter tse ntlafalitsoeng ke CV e mene tse hlano, SVM e ile ea koetlisetsoa batho bohle sehlopheng ka seng sa lihlopha tsena tse tharo. Sebaka se tlasa ROC curve (AUC) se ne se koptjoa bakeng sa mohlala o mong le o mong e le boholo ba tšebetso ea ona. Liteko tsa DeLong () ba ne ba hiriloe ho bapisa AUC lipakeng tsa mefuta ka 'ngoe. Ha AUC e ne e fapana ka ho p-value ea 0.05, ts'ebetso e ne e nkuoa e sa lekane le mefuta e 'meli.

Ho nepahala ha tlhahlobo

Lits'ebetso tsa merero ho tloha molokong le khetho ea likarolo ho aho a mofuta oa mekhahlelo li hlahisoa ka Setšoantšo Figure1.1. Bakeng sa sehlopha ka seng sa lihlopha tsena tse tharo, mefuta ea lihlopha tsa SVM e ile ea hlahisoa ho sebelisoa likarolo tse khethiloeng e le batseteli. Re ile ra lekola ho nepahala ha mefuta ea ho khetholla ka ho sebelisa moralo oa CV ea ho tlohela e le 'ngoe, e le hore mokhoa o hlakileng oa tlhahlobo o khethiloeng bakeng sa motho e mong le e mong ea siiloeng ebe o fetisoa ho batho bohle. Bohlokoa ba lipalo-palo ba ho nepahala bo ile ba hakangoa ka ho sebelisa liteko tsa tumello. Karolelano e matla ea ho hlopha pakeng tsa sehlopha ka seng sa lihlopha tsena tse tharo e ne e hlahisoa ka ho lumella mangolo a batho ka makhetlo le ho lekanya ho nepahala ho amanang le mangolo a lumelloang. Ha ho nepahala ho lekantsoeng bakeng sa mabitso a sa ngolisoang ho ne ho phahame ho feta kapa ho lekana le phepelo e nyane ka p-value ea 0.05, e neng e ikemiselitse ho fapana haholo le boemo ba monyetla (ho nepahala = 50%). Ntle le moo, matrix a pherekano a ile a bonoa ho hlalosa kutloisiso le ho hlaka mabapi le phapano lipakeng tsa sehlopha ka seng sa lihlopha tsena tse tharo.

 

Faele e kantle e nang le setšoantšo, papiso, joalo-joalo Lebitso la ntho ke fpsyt-09-00291-g0001.jpg

Lits'ebetso tsa Schematic ho tloha molokong le ho khethoa ha likarolo tsa neuroanatomical ho ahoa ha meetso bakeng sa karohano lipakeng tsa libapali tsa disordered (DG) le libapali tse sa pheleng hantle tsa lipapali (HN), lipakeng tsa libapali tse tloaelehileng (NG) le HN, le lipakeng tsa DG le NG. GM, taba e putsoa; WM, taba e tšoeu.

Results

Likhetho

Figure Figure22 e bonts'a likarolo tse khethiloeng har'a likarolo tsa 108 ka litekanyetso tsa bona tse sebetsang, le Tafole Lethathamo11 e hlalosa tlhaiso-leseling e lumellanang ea mofuta oa tloaelo oa ho hlophisa lintho o lokelang ho hlophisoa lipakeng tsa sehlopha ka seng. Ntle le moo, Setšoantšo S1 e bonts'a hore na λ e hlahisitse phoso e fokolang ea CV le hore na ho khethiloe likarolo tse kae ho feta1SE hammoho le ho fetaMinErr. Phoso e fokolang ea CV e fumanoe ho khethoa ha likarolo ke lasso (lasso weight = 1) bakeng sa karohano lipakeng tsa libapali tse sa pheleng hantle le libapali tse tloaelehileng le net net (lasso weight = 0.5) bakeng sa sehlopha se seng.

 

Faele e kantle e nang le setšoantšo, papiso, joalo-joalo Lebitso la ntho ke fpsyt-09-00291-g0002.jpg

Likarolo tse khethiloeng tsa neuroanatomical ho regression e hlophisitsoeng e hlophisehileng ea karohano lipakeng tsa sehlopha ka seng sa lihlopha tse tharo. Li-gamers tse senyehileng (DG) li ne li ngotsoe e le 1 sehlopheng pakeng tsa bao e seng libapali tse phetseng hantle (HN) le DG, libapali tse tloaelehileng (NG) joalo ka 1 sehlopheng se pakeng tsa HN le NG, le DG e le 1 sehlopheng se lipakeng tsa NG le DG. Boholo ba bareng bo emela boholo ba coefficient ea likarolo tse fapaneng, joalo ka hore likarolo tsa li-coefficients tse seng zero li khethiloe. Boko bo fetoletsoeng bo bonts'a lintho tse bohlooho le likarolo tse tšoeu tse tsamaellanang le likarolo tse khethiloeng ho tsoa ponong e phahameng. Likarolo tse khubelu kapa tse putsoa li bontša tse kenyellelitsoeng ho likarolo tsa sparser tse khethiloeng ho λ1SE hammoho le likarolo tsa sparse tse khethiloeng ho λMinErr, athe tse 'mala o mosehla kapa o magenta li bonts'a tse kenyellelitsoeng likarolo tsa sparse feela. Labels tsa likarolo tsa boko li fanoa litafoleng S1 'me S2. L, ka ho le letšehali; R, ho lokile.

Lethathamo 1

Ho lekana tlhaiso-leseling e hlophisitsoeng khafetsa bakeng sa khethollo lipakeng tsa sehlopha ka seng sa lihlopha tse tharo.

 HN vs. DGHN vs NGNG vs. DG
parametharaGMbotenyabotenyaVolume
 WMFARDMD
Boima ba Lasso0.510.5
Litšobotsi tsa Sparse tse khethiloeng ho λMinErrPhoso ea CV37.368141.7876133.3857
 Che. Ea likarolo432111
Karolo ea Sparser e khethiloeng ho λ1SEPhoso ea CV46.568150.0435141.2622
 Che. Ea likarolo34121
 

Boima ba lasso bo bontša hore na mokhoa o tloaelehileng oa ho hlophisa lintho o ile oa etsoa ho sebelisoa lasso (lasso weight = 1) kapa net elastic (lasso weight = 0.5).

HN, libapali tse sa pheleng hantle; DG, libapali tse sa tsotelleng; NG, libapali tse tloaelehileng; GM, taba e putsoa; WM, taba e tšoeu; FA, anisotropy e mabifi; RD, radial diffusivity; MD, ho bolela ho fapana; CV, netefatso ea.

Khethollong ea libapali tse sa tsotelleng tse tsoang ho libapali tse se nang phepo tse ntle, likarolo tsa 43 tse khethiloeng ho λMinErr e ne e akaretsa botenya ba libaka tsa 24 GM le lipampitšana tsa FA tsa 19 WM, le likarolo tsa 34 tse khethiloeng ho λ1SE e ne e akaretsa botenya ba libaka tsa 15 GM le lipampitšana tsa FA tsa 19 WM. Ka phapang ea libapali tse tloaelehileng ho tsoa ho bao e seng libapali tse phetseng hantle, likarolo tsa 21 tse khethiloeng ho λMinErr e ne e kenyelletsa botenya ba libaka tsa 12 GM le lits'oants'o tsa RD tsa 9 WM, le likarolo tsa 12 tse khethiloeng ho λ1SE e ne e kenyelletsa botenya ba libaka tsa 6 GM le RD lipapatso tsa 6 WM. Ka har'a sehlopha sa libapali tse sa tsotelleng le tse tloaelehileng, likarolo tsa 11 li khethiloe ho λMinErr e ne e le boholo ba libaka tsa 7 GM le lipampitšana tsa MD tsa 4 WM, le tšobotsi e le 'ngoe e khethiloeng ho λ1SE e tsamaellanang le boholo ba sebaka se le seng sa GM.

Ts'ebetso ea likarolo tse khethiloeng

Pakeng tsa sebopeho se nang le likarolo tse fokotsehileng le mohlala o nang le likarolo tsohle tsa 108, ts'ebetso e ne e bapisoa ho latela AUC ka khethollo pakeng tsa mofuta o mong le o mong oa libapali le bao e seng libapali tse phetseng hantle ke li-SVM (Setšoantšo. (Figure3) .3). Khethollong lipakeng tsa libapali tse sa tsotelleng le tse tloaelehileng, mohlala o na le likarolo tse khethiloeng mohlomong hoMinErr (AUC = 0.83, p = 0.006) kapa ho λ1SE (AUC = 0.72, p <0.001) e bonts'itse ts'ebetso e futsanehileng ho feta ea mohlala ka likarolo tsohle tsa 108 (AUC = 0.90).

 

Faele e kantle e nang le setšoantšo, papiso, joalo-joalo Lebitso la ntho ke fpsyt-09-00291-g0003.jpg

Papiso ea ts'ebetso ho latela sebaka se tlasa mochini o amohelang mofuta oa li-curve (AUC) lipakeng tsa meetso e se nang le khetho ea karolo bakeng sa karohano lipakeng tsa sehlopha ka seng sa lihlopha tse tharo ka metjhini ea vector. Moetso oa likarolo tsa 108 (o bonts'itsoeng ke mohala o tiileng) o lumellana le seo ntle le khetho ea sebopeho, athe mehlala ea linomoro tse fokotsehileng ea likarolo e lumellana le tse nang le likarolo tsa sparse le sparser tse khethiloeng ho λMinErr (e bonts'itsoe ke mola o oeleng) le λ1SE (e bonts'itsoe ke mola oa dash-dot), ka ho latellana. HN, libapali tse sa pheleng hantle; DG, libapali tse sa tsotelleng; NG, libapali tse tloaelehileng.

Ho nepahala ha tlhahlobo

Ka tatellano ke li-SVM li sebelisa likarolo tse khethiloeng ho λMinErr, ho nepahala ho ne ho le boholo ho feta 98%, e phahame haholo ho feta boemo ba monyetla (p <0.001), ka khethollo ea mofuta o mong le o mong oa libapali ho tsoa ho bao e seng libapali tse phetseng hantle (Setšoantšo (Figure4A) .4A). Ho nepahala ho ne ho ntse ho phahame haholo ho feta boemo ba menyetla (p = 0.002) empa e tlase joalo ka 69.8% ka har'a sehlopha sa libapali tse sa tsotelleng le tse tloaelehileng, se bonts'a kutloisiso e tlase (47.4%) ponts'o e nepahetseng ea libapali tse sa sebetseng. Litšobotsi tsa sparser tse boletsoeng ho λ1SE e bonts'itse ts'ebetso e ts'oanang (Setšoantšo (Figure4B) 4B) empa e bonts'itse kutloisiso e tlase haholo (2.6%) ka phapano e nepahetseng ea libapali tse sa arohaneng ho tsoa ho libapali tse tloaelehileng.

 

Faele e kantle e nang le setšoantšo, papiso, joalo-joalo Lebitso la ntho ke fpsyt-09-00291-g0004.jpg

Li-matric tsa pherekano bohlopheng ba lihlopha tse tharo ha li sebelisoa (A) sparse le (B) likarolo tsa sparser tse boletsoeng ho λMinErr le ho inth1SE, ka ho latellana, mochini oa li-vector oa tšehetso. Seli e ka letsohong le letona e emela ho nepahala ha maemo (ACC), sekhahla se tlase sa leqele ka 'nete (TNR) kapa boemo bo tobileng, sekhahla se tlase sa "cell cell" se nepahetseng sa boleng bo phahameng (NPV) ), le boleng bo lekanyang ba sele e nepahetseng ea bokapele (PPV). TP, ntle le nnete; TN, 'nete e mpe; FP, maikutlo a fosahetseng; FN, fosahetseng.

Puisano

Phuputsong ena, re batlile ho hlahloba hore na libapali tsa methapo ea methapo le tseo e seng tsa methapo-kutlo joalo ka karolo ea IGDS e hlahisitsoeng ho DSM-5 li ka emeloa ke likarolo tsa sparse neuroanatomical. Libapali tse sa tsotelleng le tse tloaelehileng li ne li emeloe ho latela likarolo tsa 43 le 21, ka ho latellana, mabapi le bao e seng libapali tse phetseng hantle. Ntle le moo, libapali tse sa tsotelleng li ne li emeloa ho latela likarolo tsa 11 mabapi le libapali tse tloaelehileng. Ho sebelisa likarolo tse fokolang tsa neuroanatomical, libapali tse sa arohaneng le tse tloaelehileng li ka khetholloa ka katleho ho bao e seng libapali tse phetseng hantle, empa khethollo lipakeng tsa libapali tse sa arohaneng le tse tloaelehileng e ne e le phephetso.

Karolo e hlalosang e thehiloeng ka matšoao ea IGD le IGDS e hlahisitsoeng ho DSM-5 e ntse e amoheloa ka bongata. Leha bonnete ba bonnete ba IGDS bo tiisitsoe linaheng tse ngata (, , ), monyetla oa ho bona lintho tsa IGDS tse hlano kapa ho feta e kanna ea se be khetho e hlakileng, 'me ho ka khothaletsoa mekhoa e meng ea ho khetholla batho ba bapalang lipapali tse thehiloeng ho Internet ((). Kaha mefuta e mengata ea tlhaiso-leseling, e kang data ea ho nahana ka bokong le tlhaiso-leseling, e fana ka tlhaiso-leseling, tlhaiso-leseling e eketsehileng e ka sebelisoa molemong oa tlhahlobo ea mafu a kelello. Haholo-holo, ka lebaka la bongata ba tlhaiso-leseling e batsi, datha ea monahano oa bokong e loketse mekhoa ea boithuto 'me e ka ba molemo bakeng sa ho bolela esale pele. Ka sebele, tlhaiso-leseling ea kelello ea bokong e bontšitsoe hore e na le boleng bo phahameng ba ho bapisa lintho ha bo bapisoa le datha tse ling tsa kliniki ponelopeleng ea ho rarolla bothata bo amanang le bongaka ().

Joalo ka ha tlhahlobo ea tlhahlobo-leseling e thehiloeng ho ML e sa tsoa sebelisoa lits'ebetsong tse ling tsa boits'oaro le likotsi (-), ho hlophisoa ha matšoao ka IGD ho boetse ho bonahala le tobane le phephetso ea karohano e thehiloeng morerong. Hobane lits'oants'o tsa tlhaho tsa boko tse latelang IGD li tlalehiloe khafetsa lithutong tse fetileng (-, ), re nkile boitsebiso bo joalo ba neuroanatomical ho tsoa ho datha imaging ea bokamoso ba biomarkers bakeng sa tlhahlobo ea IGD. Phuputsong ena, sepheo sa rona e ne e le ho khetholla likarolo tsa bohlokoa tsa neuroanatomical tse ka fanang ka ts'ebetso e phahameng ea sehlopha, ntle le ho hlalosa liphapang tsa neuroanatomical lipakeng tsa lihlopha tsa batho.

Re khethile tse bohlokoa, har'a likarolo tsa 108 tsa neuroanatomical, re regression e hlophisitsoeng hantle. Ha re nahana ka mefuta e robeli ea li-paramethara tsa GM le WM, mefuta e fapaneng ea litekanyetso li ile tsa khethoa bakeng sa ho khetholla sehlopha ka seng sa lihlopha tsena tse tharo. Ho kopantsoe ha botenya ba libaka tsa GM le botsitso ba lipampitšana tsa WM ho ne ho le betere ho khetholla libapali tsa methapo ho tsoa ho bao e seng libapali tse phetseng hantle, athe ho kopana ha boholo ba libaka tsa GM le ho fapana ha lipampitšana tsa WM ho ne ho le betere ho khetholla libapali tsa pathological ho tsoa ho libapali tse seng tsa methapo. Ntle le moo, le ha likarolo tse ngata tsa boko li ne li sebelisoa hangata e le likarolo tsa neuroanatomic tse neng li le bohlokoa bakeng sa karohano ea libapali tsa methapo ea methapo le tseo e seng tsa methapo ho tsoa ho libapali tse sa pheleng hantle, libaka tse ling tsa GM le lipampitšana tsa WM li ne li tšoaea libapali tseo e seng tsa methapo, empa eseng libapali tsa methapo ea kutlo. . Liphumano tsena li bonts'a hore ha ho na ho ba le kopants'o e sebetsang hantle ka ho fetisisang ea li-parameter tsa GM le WM joalo ka li-biomarkers tsa neuroanatomical, e le hore motsoako o ikhethang oa li-parameter tsa GM le WM o hloka ho khethoa ho latela lihlopha tse khethiloeng.

Palo e nyane ea likarolo tsa sparse bakeng sa karohano ea libapali tse se nang ts'oaetso ha li bapisoa le phapang ea libapali tsa methapo, ho tsoa ho libapali tse sa pheleng hantle, li bonts'a hore libapali tse seng tsa methapo ea methapo li maemong a phetoho lipakeng tsa libapali tsa methapo le tse phetseng hantle. e seng libapali. Ntle le moo, likarolo tse fokolang tsa phapanyetsano lipakeng tsa mefuta e 'meli ea libapali ho fapana le khethollo lipakeng tsa mofuta o mong oa libapali le libapali tse sa pheleng li bontša hore libapali tsa methapo ea kutlo le tse se nang mabaka li ne li sa khahlise e mong le e mong ka mantsoe ea neuroanatomy ho feta ho bona ba sa tšoane le libapali tse sa pheleng hantle. Ka hona, mehlala ea sehlopha e hlahisitsoeng ka likarolo tsa sparse e hlahisitse ho nepahala ho feta 98% khethollong lipakeng tsa mofuta o mong le o mong oa libapali le bao e seng libapali tse nepahetseng empa ka nepahalo e ka tlase ho 70% ka tatellano lipakeng tsa mefuta e 'meli ea libapali. Ka mantsoe a mang, libapali tseo e seng tsa methapo ea kutlo li ne li khetholoha ho libapali tse sa pheleng hantle joalo ka libapali tse neng li le teng, empa ho ne ho e-na le meeli ea ho khetholla lipakeng tsa libapali tsa methapo ea methapo eo e seng ea methapo.

Phapang ena e batlang e le tlase haholo pakeng tsa mefuta e 'meli ea libapali ho bonahala e fana ka maikutlo a seng makae. Taba ea mantlha, karohano pakeng tsa karohano e thehiloeng lipontšo le karohano e thehiloeng ka har'a komporo e kanna ea ananeloa. Le ha mokhoa oa tlhahlobo oa tlhahlobo ea tlhahlobo ea tlhahlobo ea mekhoa e mehlano kapa ho feta ho IGDS o ile oa khethoa ka mokhoa o hlokolosi ho thibela tlhahlobo ea IGD (ho feta)), boteng ba libapali tse utloang liphetoho tse kholo tsa methapo ho neuroanatomy empa li sa khotsofatse monyako oa IGD li kanna tsa se tsotelloe. Haholo-holo re kenyelelitse libapali feela tse ileng tsa khotsofatsa lintho tsa IGDS tse tlase haholo ho feta mokhoa oa IGD joaloka libapali tse tloaelehileng, e le hore libapali li fumanoe li se na IGD ka kakaretso li hole le batho ba sa pheleng ho feta ba bonts'itsoeng thutong ena. Taba ea bobeli, phephetso ea ho khetholla batho ba itšetlehileng ka li-biomarkers tsa neuroanatomical feela. Ts'ebetso ea boits'oaro e ka ntlafatsoa ka ho kenyelletsa li-biomarkers tse ling tse ka khethollang ho se lekane pakeng tsa libapali tsa methapo ea maoto le tse seng tsa 'mele. Haholo-holo hobane liphetoho tse sebetsang bokong le tsona li bontšoa ho IGD (-), Ho sebetsa hantle le boiphihlelo ba bokong ho ka nkuoa e le li-biomarkers tsa boko. Ntle le moo, re batla ho hlokomela hore liphetoho tse bokong e mpa feela e le karolo ea likarolo tse ngata tsa bokhoba ba papali ea marang-rang, e le hore lintlha tse ling, li se ke tsa ba le likotsi tse ngata tsa kahare le kantle tsa ho lemalla papali ea inthanete (), e lokela ho kenyelletsoa mefuteng e felletseng ea khethollo lipakeng tsa libapali tsa methapo le tseo e seng tsa methapo hammoho le phapang ea libapali ho batho ba sa pheleng ba lipapali.

Mona, re sebelisitse khafetsa khafetsa, re sebelisa likhakanyo tsa sparsity tse khothatsang tse kang lasso le elastic net, ho tseba likarolo tsa bohlokoa bakeng sa mehlala ea sehlopha. Ho hlile ho na le phapang ea mokhoa oa ho khetha likarolo kapa phokotso ea boholo, mme mekhoa e fapaneng e ka sebelisoa bakeng sa ts'ebeliso ea likarolo tse khethiloeng ho aho mohlala.). Mokhoa oa rona oa ho sebelisa tloaelo e tloaelehileng e kenyelletsa khopolo ea pele mabapi le sparsity ho likarolo tsa neuroanatomical. Ha feela monahano o joalo o amoheleha, joalo ka ha re ne re lumela phuputsong ena, ho ikhopola khafetsa e ka ba mokhoa o hlakileng, 'me likarolo tse khethiloeng tsa sparse li ka lebelloa ho etsa mefuta e khethiloeng ea ts'ebetso e phahameng. Empa hoa hlokomeleha hore mefuta e bonolo ea ho khetholla e thehiloeng ho sparsity e kholo e ka 'na ea se ke ea lula e bonts'a ts'ebetso e ts'oanang kapa e ntlafalitsoeng. Ho joalo, har'a liqeto tse fapaneng tsa tekanyo ea sparsity ho latela paramente ea tloaelo, sparsity e kholo e ne e se na monyetla oa ho fana ka mohlala o sebetsang o ikhethang ka ho khetheha mathateng a khethollang haholoanyane a khethollo, joalo ka karohano lipakeng tsa libapali tsa methapo ea methapo le e seng ea methapo.

Ntle le moo, re sebelisitse li-SVM e le mokhoa oa ML bakeng sa ho aha mefuta ea lihlopha, hobane ke e 'ngoe ea tse tummeng haholo. Mekhoa e meng e tsoetseng pele e kanna ea sebelisoa ho ntlafatsa ts'ebetso ea mekhahlelo, leha ts'ebetso ea papiso lipakeng tsa mekhoa e fapaneng e kanna ea se ke ea phethoa ka lebaka la ts'epahalo ea ts'ebetso maemong a liteko.). Ka lehlakoreng le leng, bakeng sa ts'ebetso ea papiso lipakeng tsa mekhoa ea khale ea lipalo le mekhoa ea ML, re tsamaisitse karohano ka ho hlophisa lintho le ho bontša hore mekhoa e 'meli, e leng ho ngola lintho ka mokhoa o hlakileng le SVM, e ne e tšoana le ts'ebetsong ea kemiso (Setšoantšo. S2). Ho kanna ha e-ba le taba ea hore mekhoa ea khale ea lipalopalo ha e tlase hangata ho mekhoa ea ML ts'ebetsong ea kemiso ().

Phuputsong ea hona joale, re senotse hore karolo ea IGD e ka hlahisoang ka lipontšo mabapi le sparse neuroanatomical biomarkers e qapileng mefuta ea lihlopha. Ntle le moo, re bonts'itse hore libapali tse seng tsa methapo ea kutlo li ka khetholoha ho libapali tsa methapo ho fapana le tsa batho ba sa pheleng papali ka papali ea neuroanatomy. Ka hona re fana ka maikutlo a hore leha litsamaiso tsa hona joale tsa ho hlahloba li itšetleha ka karohano e hlalosang e joalo ka DSM-5 joalo ka litekanyetso tsa khauta, libapali tse seng tsa methapo li ka hloka ho fumanoa ka tlhokomelo e eketsehileng ka ho sebelisa li-biomarkers tsa sepheo tse kang tse amanang le liphetoho tsa neuroanatomical. Ho amoheloa ha mekhoa ea ho kopanya ho bonahala e le mokhoa o ke keng oa fetoha oa litšebelisano tsa kelello, empa ho ka ba le tsela e telele eo o lokelang ho e etsa ea ho sebelisa lits'ebeletso tsa bongaka. Batla khetho e nepahetseng ea likarolo tsa sparse ho tsoa monahanong oa bokong le tlhaiso-leseling ea bongaka e hloka ho etsoa lithutong tse latelang, mme kamora nako e telele, boiteko bona bo ne bo tla khothaletsa tlhahlobo e thehiloeng ho complication ea IGD.

Menehelo ea Mongoli

D-JK le J-WC ba ne ba ikarabella molemong oa thuto le moralo. HC e tsamaisitse tlhahlobo le khetho ea barupeluoa. CP e ile ea sekaseka tlhaiso-leseling eo 'me ea ngola mengolo e ngotsoeng. Bangoli bohle ba ile ba lekola ka hloko se ngotsoeng le ho amohela mofuta oa ho qetela oa phatlalatso.

Khohlano ea polelo ea thahasello

Bangoli ba bolela hore lipatlisiso li ne li etsoa ka ho se be le likamano leha e le life tsa khoebo kapa tsa lichelete tse ka nkoang e le khohlano e ka 'nang ea e-ba le thahasello.

Mongolo o botlaaseng ba leqephe

 

Lithuso. Patlisiso ena e ne e tšehelitsoe ke Lenaneo la Lipatlisiso tsa Brain ka National Research Foundation ea Korea (NRF) e tšehelitsoeng ke Lefapha la Saense le ICT ea Korea (NRF-2014M3C7A1062893).

 

 

Lintho tse ling tse eketsehileng

The Supplementary Material bakeng sa sehlooho sena se ka fumaneha Inthaneteng ka: https://www.frontiersin.org/articles/10.3389/fpsyt.2018.00291/full#supplementary-material

References

1. Mocha KS. Tlatsetso ea inthanete: ho hlaha ha bokuli bo bocha ba kliniki. CyberPsychol Behav. (1998) 1: 237-44. 10.1089 / cpb.1998.1.237 [Ref Ref Cross]
2. American Psychiatric Association Diagnostic and Statistical Manual ea Mathata a Kelello, 5th Edition. Washington, DC: Ho phatlalatsa Mokhatlo oa Mahlale a Amerika; (2013).
3. Ko CH, Yen JY, Chen SH, Wang PW, Chen CS, Yen CF. Teko ea tekanyetso ea tlhahlobo ea bosholu ba lipapali tsa inthanete ho DSM-5 har'a bacha ba baholo ba Taiwan. J Psychiatr Res. (2014) 53: 103-10. 10.1016 / j.jpsychires.2014.02.008 [E fetotsoe] [Ref Ref Cross]
4. Ko CH, Hsieh TJ, Wang PW, Lin WC, Yen CF, Chen CS, et al. . Tekanyo e fetotsoeng ea lintho tse putsoa le ho sitisoa ha likhokahano tsa amygdala ho batho ba baholo ba nang le bothata ba lipapali tsa inthanete. Prog Neuropsychopharmacol Biol Psychiatry (2015) 57: 185-92. 10.1016 / j.pnpbp.2014.11.003 [E fetotsoe] [Ref Ref Cross]
5. Lin X, Dong G, Wang Q, Du X. Ho sa tloaelehang taba e putsoa le bosoasoi le taba e tšoeu ho 'ba lemaletseng lipapali tsa papali ea inthanete'. Moemeli oa Behav. (2015) 40: 137-143. 10.1016 / j.addbeh.2014.09.010 [E fetotsoe] [Ref Ref Cross]
6. Wang H, Jin C, Yuan K, Shakir TM, Mao C, Niu X, et al. . Phetoho ea molumo oa litaba tsa bohlooho le taolo ea kelello ho bacha ba nang le bothata ba lipapali tsa marang-rang. Front Behav Neurosci. (2015) 9: 64. 10.3389 / fnbeh.2015.00064 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
7. Yuan K, Cheng P, Dong T, Bi Y, Xing L, Yu D, et al. . Bohloko ba boteng ba cortical bothateng ba ho kena bohlankaneng kapa bokhobeng ba marang-rang. PloS One (2013) 8: e53055. 10.1371 / journal.pone.0053055 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
8. Dong G, Devito E, Huang J, Du X. Phapang e tenang ea maikutlo e senola thalamus le lits'oants'o tsa morao-rao tsa cingate tsa cortex ho litlhare tsa papali ea marang-rang. J Psychiatr Res. (2012) 46: 1212-6. 10.1016 / j.jpsychires.2012.05.015 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
9. Xing L, Yuan K, Bi Y, Yin J, Cai C, Feng D, et al. . Fokotsa botsitso ba fiber le taolo ea kelello ho bacha ba nang le bothata ba lipapali tsa marang-rang. Brain Res. (2014) 1586: 109-17. 10.1016 / j.brainres.2014.08.044 [E fetotsoe] [Ref Ref Cross]
10. Besson P, Dinkelacker V, Valabregue R, Thivard L, Leclerc X, Baulac M, et al. . Phapang ea khokahano ea moralo ho lisele tsa sethoathoa sa sethoathoa sa letsoho. Neuroimage (2014) 100: 135-44. 10.1016 / j.neuroimage.2014.04.071 [E fetotsoe] [Ref Ref Cross]
11. Huys QJ, Maia TV, Frank MJ. Tlhabollo ea mafu a kelello ea kelello e le borokho bo tlohang ho neuroscience ho isa lits'ebetsong tsa bongaka. Nat Neurosci. (2016) 19: 404-13. 10.1038 / nn.4238 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
12. Lemmens JS, Valkenburg PM, DA ea Balichaba. Lenane la bosholu ba lipapali tsa inthanete. Tlhahlobo ea Psychol. (2015) 27: 567-82. 10.1037 / pas0000062 [E fetotsoe] [Ref Ref Cross]
13. Dahnke R, Yotter RA, Gaser C. botenya ba cortical le khakanyo ea bokaholimo ba lefatše. Neuroimage (2013) 65: 336-48. 10.1016 / j.neuroimage.2012.09.050 [E fetotsoe] [Ref Ref Cross]
14. Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, et al. . Lipalopalo tse ipapisitseng le sebaka sa tšebeliso ea tšebeliso ea litaba: tlhahlobo ea voxelwise ea lintlha tse ngata tsa tlhaiso-leseling. Neuroimage (2006) 31: 1487-505. 10.1016 / j.neuroimage.2006.02.024 [E fetotsoe] [Ref Ref Cross]
15. Hammers A, Allom R, Koepp MJ, SL ea mahala, Myers R, Lemieux L, et al. . Litlhaselo tse kholo tse nang le likarolo tse tharo tsa boko ba motho, ha li bua haholo ka lobe ea nakoana. Hum Brain Mapp. (2003) 19: 224-47. 10.1002 / hbm.10123 [E fetotsoe] [Ref Ref Cross]
16. Mori S, Oishi K, Jiang H, Jiang L, Li X, Akhter K, et al. . Litaba tse tšoeu tsa Stereotaxic tse ipapisitseng le likhopolo tsa infensor tensor ka template ea ICBM. Neuroimage (2008) 40: 570-82. 10.1016 / j.neuroimage.2007.12.035 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
17. Tibshirani R. Regression shrinkage le khetho ka lasso. J Roy Stat Soc Ser B (1996) 58: 267-88.
18. Zou H, Hastie T. Ts'ebetso ea kamehla le khetho e fapaneng ka net. J Roy Stat Soc Ser B (2005) 67: 301-20. 10.1111 / j.1467-9868.2005.00503.x [Ref Ref Cross]
19. Theodoridis S. Machine Ho Ithuta: Tlhahlobo ea Bayesian le Optimization. London: Thutong ea Litaba; (2015).
20. Delong ER, Delong DM, Clarke-Pearson DL. Ho bapisa libaka tse katiloeng ka li-curve tse peli kapa ho feta tse kopantsoeng: mokhoa o se nang phapang. Li -ometri (1988) 44: 837-45. 10.2307 / 2531595 [E fetotsoe] [Ref Ref Cross]
21. Cho SH, Kwon JH. Netefatso ea phetolelo ea Korea ea Internet Gaming Disorder Scale (K-IGDS): liphetho ho tsoa mehlala ea batho ba baholo. Kore J Clin Psychol. (2017) 36: 104-17. 10.15842 / kjcp.2017.36.1.010 [Ref Ref Cross]
22. Sigerson L, Li AYL, Cheung MWL, Luk JW, Cheng C. Psychometric thepa ea boemo ba papali ea likotsi tsa inthanete. Moemeli oa Behav. (2017) 74: 20-6. 10.1016 / j.addbeh.2017.05.031 [E fetotsoe] [Ref Ref Cross]
23. Burke Quinlan E, Dodakian L, Bona J, Mckenzie A, Le V, Wojnowicz M, et al. . Ts'ebetso ea Neural, likotsi, le stroke "subtype" li bolela esale pele melemo ea kalafo kamora ho otloa. Ann Neurol. (2015) 77: 132-45. 10.1002 / ana.24309 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
24. Pariyadath V, Stein EA, Ross TJ. Ts'ebetso ea ho ithuta ka mochini bakeng sa ho ikopanya ha tšebetso ea mmuso e bolela esale pele boemo ba ho tsuba. Front Hum Neurosci. (2014) 8: 425. 10.3389 / fnhum.2014.00425 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
25. Fedota JR, Stein EA. Khokahano e sebetsang ea mmuso le ts'ebeliso ea lithethefatsi tsa nicotine: litebello tsa nts'etsopele ea biomarker. Ann NY Acad Sci. (2015) 1349: 64-82. 10.1111 / nyas.12882 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
26. Ahn WY, Ramesh D, Moeller FG, Vassileva J. Ts'ebeliso ea mekhoa ea ho ithuta ka mochini ho khetholla matšoao a boits'oaro bakeng sa mathata a ts'ebeliso ea lithethefatsi: litekanyetso tsa ho se ts'oenyehe e le baphethahatsi ba ts'ebeliso ea koae ea hona joale. Front Psychiatry (2016) 7: 34. 10.3389 / fpsyt.2016.00034 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
27. Ahn WY, Vassileva J. Machine-ithuta e supa matšoao a ikhethang a boits'oaro bakeng sa ts'ebetso ea ts'ebetso ea opiate le ts'usumetso e matlafatsang. Lithethefatsi. (2016) 161: 247-57. 10.1016 / j.drugalcdep.2016.02.008 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
28. Percy C, França M, Dragičević S, D'avila Garcez A. Ho bolela esale pele papali ea chelete ea inthanete ho itšehla thajana: tlhahlobo ea ts'ebetso ea mehlala e laoloang ea ho ithuta mochini. Int Gambl Stud. (2016) 16: 193-210. 10.1080 / 14459795.2016.1151913 [Ref Ref Cross]
29. Ding WN, Sun JH, Sun YW, Zhou Y, Li L, Xu JR, et al. . Khokahano e fetotsoeng ea marang-rang ea ho phomola e sebetsang ea maemo ho bacha lilemong ba lemaletseng lipapali tsa marang-rang. PloS One (2013) 8: e59902. 10.1371 / journal.pone.0059902 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
30. Meng Y, Deng W, Wang H, Guo W, Li T. Tlhatlhobo ea pele ho batho ka bomong ba nang le bothata ba lipapali tsa marang-rang: tlhahlobo ea meta-lithuto tsa ts'ebetso ea ho nahana ka matla a boloi. Adict Biol. (2015) 20: 799-808. 10.1111 / adb.12154 [E fetotsoe] [Ref Ref Cross]
31. Zhang JT, Yao YW, Li CSR, Zang YF, Shen ZJ, Liu L, et al. . Boemo bo fetoletsoeng ba mmuso ba ho ikopanya ha mosebetsi oa ho kenella ho batho ba baholo ba nang le bothata ba lipapali tsa inthanete. Adict Biol. (2015) 21: 743-51. 10.1111 / adb.12247 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
32. Cai C, Yuan K, Yin J, Feng D, Bi Y, Li Y, et al. . Striatum morphometry e amahanngoa le bofokoli ba taolo ea kelello le ho teba ha matšoao a marang-rang a lipapali tsa marang-rang. Ho Behav Brain (2016) 10: 12-20. 10.1007 / s11682-015-9358-8 [E fetotsoe] [Ref Ref Cross]
33. Park C, Chun JW, Cho H, Jung YC, Choi J, Kim DJ. Na boko bo lemaletseng papali ea marang-rang bo haufi le ho ba maemong a phelisang? Adict Biol. (2017) 22: 196-205. 10.1111 / adb.12282 [E fetotsoe] [Ref Ref Cross]
34. Kuss DJ, Griffiths MD. Tlatsetso ea papali ea papali ea inthanete: tlhahlobo e hlophisehileng ea lipatlisiso tse susumetsang. Int J Ment Health Adict. (2012) 10: 278-96. 10.1007 / s11469-011-9318-5 [Ref Ref Cross]
35. Castellanos FX, Di Martino A, Craddock RC, Mehta AD, MP oa Milham. Lisebelisoa tsa kliniki tsa sehokahanyo se sebetsang. Neuroimage (2013) 80: 527-40. 10.1016 / j.neuroimage.2013.04.083 [Tlhahiso ea mahala ea PMC] [E fetotsoe] [Ref Ref Cross]
36. Tollenaar N, Van Der Heijden P. Ke mokhoa ofe o rerang hore li-recidivism li ka sebetsa hantle? J Roy Stat Soc Ser A (2013) 176: 565-84. 10.1111 / j.1467-985X.2012.01056.x [Ref Ref Cross]