Enkosi ngokundwendwela i-Nature.com.Inguqulelo yesikhangeli oyisebenzisayo inenkxaso enyiniweyo yeCSS.Ngeziphumo ezingcono, sicebisa ukuba usebenzise inguqulelo entsha yesikhangeli sakho (okanye ucime imo ehambelanayo kwi-Internet Explorer).Okwangoku, ukuqinisekisa inkxaso eqhubekayo, sibonisa indawo ngaphandle kwesitayile okanye iJavaScript.
Izicelo zobukrelekrele bezonyango (i-AI) zikhula ngokukhawuleza, kodwa ikharityhulamu esele ikho yesikolo sezonyango ibonelela ngokufundisa okulinganiselweyo okugubungela lo mmandla.Apha sichaza ikhosi yoqeqesho lobukrelekrele eyenziweyo esiyiphuhlisileyo saza sayihambisa kubafundi bezonyango baseKhanada kwaye senze iingcebiso zoqeqesho lwexesha elizayo.
Ubukrelekrele bokwenziwa (AI) kwezamayeza kunokuphucula ukusebenza kakuhle kunye nokunceda ekwenzeni izigqibo zonyango.Ukukhokela ngokukhuselekileyo ukusetyenziswa kobukrelekrele bokwenziwa, oogqirha kufuneka babe nokuqonda okuthile ngobukrelekrele bokwenziwa.Amagqabantshintshi amaninzi axhasa ukufundisa i-AI concepts1, njengokucacisa iimodeli ze-AI kunye neenkqubo zokuqinisekisa2.Nangona kunjalo, zimbalwa izicwangciso ezicwangcisiweyo ezithe zaphunyezwa, ingakumbi kwinqanaba lesizwe.UPinto dos Santos et al.3.Abafundi bezonyango abangama-263 bavavanywa kwaye i-71% bavuma ukuba bafuna uqeqesho kubukrelekrele bokwenziwa.Ukufundisa ubukrelekrele bokwenziwa kubaphulaphuli bezonyango kufuna uyilo olunenkathalo oludibanisa iikhonsepthi zobugcisa kunye nezingezizo ezobuchwephesha kubafundi abasoloko benolwazi olubanzi lwangaphambili.Sichaza amava ethu ngokuhambisa uluhlu lweeworkshops ze-AI kumaqela amathathu abafundi bezonyango kwaye senze iingcebiso kwimfundo yezonyango kwixesha elizayo kwi-AI.
Intshayelelo yethu yeeveki ezintlanu kwi-Artificial Intelligence in Medicine workshop yabafundi bezonyango yabanjwa kathathu phakathi kukaFebruwari 2019 noAprili 2021. Ishedyuli yeeworkshop nganye, enenkcazo emfutshane yotshintsho kwikhosi, iboniswe kuMfanekiso 1. iinjongo ezintathu zokufunda eziziiprayimari: abafundi bayayiqonda indlela idatha ecutshungulwa ngayo kwizicelo zobukrelekrele bokwenziwa, bahlalutye uncwadi lobukrelekrele bokwenziwa kwizicelo zeklinikhi, kwaye basebenzise amathuba okusebenzisana neenjineli eziphuhlisa ubukrelekrele bokwenziwa.
IBlue sisihloko sentetho kunye nokukhanya okuluhlaza okwesibhakabhaka ngumbuzo osebenzisanayo kunye nexesha lokuphendula.Icandelo elingwevu yingqwalasela yophononongo olufutshane loncwadi.Amacandelo e-orenji akhethiweyo angumzekelo wezifundo ezichaza imodeli okanye ubuchule bobukrelekrele bokwenziwa.Uhlaza yikhosi yenkqubo ekhokelwayo eyenzelwe ukufundisa ubukrelekrele bokwenziwa ukusombulula iingxaki zeklinikhi kunye nokuvavanya iimodeli.Umxholo kunye nobude beendibano zocweyo ziyahluka ngokusekelwe kuvavanyo lweemfuno zabafundi.
Iworkshop yokuqala yabanjwa kwiDyunivesithi yaseBritish Columbia ukusuka ngoFebruwari ukuya kuEpreli 2019, kwaye bonke abathathi-nxaxheba abasi-8 banike ingxelo eyakhayo4.Ngenxa ye-COVID-19, indibano yocweyo yesibini yabanjwa phantse ngo-Okthobha-Novemba ka-2020, inabafundi bezonyango abangama-222 kunye nabahlali aba-3 abavela kwizikolo ezisibhozo zaseKhanada ezibhalisayo.Izilayidi zentetho kunye nekhowudi zifakwe kwindawo evulekileyo yofikelelo (http://ubcaimed.github.io).Ingxelo ephambili evela kuphindaphindo lokuqala yayikukuba iintetho bezibukhali kakhulu kwaye imathiriyeli iyithiyori kakhulu.Ukukhonza imimandla yamaxesha amathandathu awahlukeneyo yaseKhanada kubangela ucelomngeni olongezelelekileyo.Ngaloo ndlela, i-workshop yesibini yanciphisa iseshoni nganye kwiyure ye-1, yenza lula izinto zekhosi, zongeza izifundo ezingaphezulu, kwaye zenze iinkqubo ze-boilerplate ezivumela abathathi-nxaxheba ukuba bazalise i-code snippets kunye ne-debugging encinci (Ibhokisi 1).Ingxelo ephambili evela kwi-iteration yesibini ibandakanya impendulo eyakhayo malunga nokusebenza kweprogram kunye nesicelo sokubonisa ukucwangciswa kweprojekthi yokufunda ngomatshini.Ke ngoko, kwindibano yethu yesithathu yocweyo, ebibanjwe malunga ne-126 labafundi bezonyango ngoMatshi-Aprili 2021, siye sabandakanya iiseshini zokusebenzisa iikhowudi kunye neeseshini zokunika ingxelo ngeprojekthi ukubonisa ifuthe lokusebenzisa iikhonsepthi zocweyo kwiiprojekthi.
Uhlalutyo lwedatha: Inkalo yokufunda kwizibalo ezichonga iipateni ezinentsingiselo kwidatha ngokuhlalutya, ukusetyenzwa, kunye nokunxibelelana kweepateni zedatha.
Ukumbiwa kwedatha: inkqubo yokuchonga kunye nokukhupha idatha.Kumxholo wobukrelekrele bokwenziwa, oku kudla ngokuba kukhulu, kunezinto ezininzi ezahlukeneyo kwisampulu nganye.
Ukuncitshiswa kobungakanani: Inkqubo yokuguqula idatha eneempawu ezininzi zomntu zibe ziimpawu ezimbalwa ngelixa ugcina iimpawu ezibalulekileyo zeseti yedatha yokuqala.
Iimpawu (kwimeko yobukrelekrele bokwenziwa): iipropathi ezinokulinganiswa zesampulu.Idla ngokusetyenziswa ngokutshintshanayo “nepropathi” okanye “inguquko”.
Imephu ye-Gradient Activation: Ubuchule obusetyenziselwa ukutolika iimodeli zobukrelekrele bokwenziwa (ingakumbi iinethiwekhi ze-neural ze-convolution), ehlalutya inkqubo yokuphucula indawo yokugqibela yothungelwano ukuchonga imimandla yedatha okanye imifanekiso eqikelelwa kakhulu.
Umzekelo oMgangatho: Imodeli ekhoyo ye-AI esele iqeqeshelwe ukwenza imisebenzi efanayo.
Uvavanyo (kumxholo wobukrelekrele bokwenziwa): ukujonga indlela imodeli eyenza ngayo umsebenzi usebenzisa idatha engazange ihlangane nayo ngaphambili.
Uqeqesho (kwimeko yobukrelekrele bokufakelwa): Ukubonelela ngemodeli ngedatha kunye neziphumo ukwenzela ukuba imodeli ilungelelanise iiparamitha zayo zangaphakathi ukuze ikwazi ukwenza imisebenzi isebenzisa idatha entsha.
IVector: uluhlu lwedatha.Kufundo lomatshini, uluhlu ngalunye lwento ludla ngokuba luphawu olulodwa lwesampulu.
IThebhile 1 idwelisa iikhosi zamva nje zika-Epreli 2021, kubandakanywa neenjongo zokufunda ezithagethiweyo kwisihloko ngasinye.Le workshop yenzelwe abo batsha kwinqanaba lobugcisa kwaye ayifuni naluphi na ulwazi lwemathematika ngaphaya konyaka wokuqala wesidanga sezonyango.Ikhosi yaphuhliswa ngabafundi bezonyango aba-6 kunye nootitshala aba-3 abanezidanga eziphambili kubunjineli.Iinjineli ziphuhlisa ithiyori yobukrelekrele bokwenziwa ukuze bafundise, kwaye abafundi bezonyango bafunda imathiriyeli efanelekileyo ngokwezonyango.
Iindibano zocweyo ziquka iintetho, izifundo, kunye nenkqubo ekhokelwayo.Kwintetho yokuqala, sihlaziya iikhonsepthi ezikhethiweyo zohlalutyo lwedatha kwi-biostatistics, kubandakanywa ukubonwa kwedatha, ukuguqulwa kwezinto, kunye nokuthelekisa izibalo ezichazayo kunye ne-inductive.Nangona uhlalutyo lwedatha lusisiseko sobukrelekrele bokwenziwa, asizibandakanyi izihloko ezinjengokumbiwa kwedatha, uvavanyo lokubaluleka, okanye ukubonwa okusebenzisanayo.Oku kwakungenxa yokunqongophala kwexesha nangenxa yokuba abanye abafundi abangekabinazidanga babenoqeqesho lwangaphambili kwi-biostatistics kwaye babefuna ukugubungela izihloko ezingakumbi zokufunda ngoomatshini.Intetho elandelayo yazisa iindlela zanamhlanje kwaye ixoxa ngokuqulunqwa kwengxaki ye-AI, izibonelelo kunye nokunciphisa iimodeli ze-AI, kunye novavanyo lwemodeli.Ezi ntetho zincediswa luncwadi kunye nophando olusebenzayo kwizixhobo ezikhoyo zobuntlola ezenziweyo.Sigxininisa izakhono ezifunekayo ukuvavanya ukusebenza kunye nokwenzeka komzekelo ukujongana nemibuzo yeklinikhi, kubandakanywa nokuqonda imida yezixhobo ezikhoyo zobukrelekrele bokwenziwa.Ngokomzekelo, sicele abafundi ukuba batolike izikhokelo zokulimala kwentloko yabantwana ezicetywayo nguKupperman et al., 5 ephumeze isigqibo somthi we-artificial intelligence ukugqiba ukuba i-CT scan iya kuba luncedo ngokusekelwe kuvavanyo lukagqirha.Sigxininisa ukuba lo ngumzekelo oqhelekileyo we-AI wokubonelela ngohlalutyo oluqikelelweyo ukuze oogqirha batolike, kunokuba batshintshe oogqirha.
Kwimizekelo ekhoyo evulelekileyo yenkqubo ye-bootstrap (https://github.com/ubcaimed/ubcaimed.github.io/tree/master/programming_examples), sibonisa indlela yokwenza uhlalutyo lwedatha yokuhlola, ukunciphisa ubukhulu, ukulayishwa kwemodeli eqhelekileyo, kunye noqeqesho. .kunye novavanyo.Sisebenzisa iincwadi zamanqaku zeGoogle Collaboratory (Google LLC, Mountain View, CA), evumela ikhowudi yePython ukuba iqhutywe kwisikhangeli sewebhu.KuMfanekiso 2 ubonelela ngomzekelo womsebenzi wokucwangcisa.Lo msebenzi ubandakanya ukuxela kwangaphambili ububi usebenzisa i-Wisconsin Open Breast Imaging Dataset6 kunye ne-algorithm yomthi wesigqibo.
Nikela iinkqubo evekini kwizihloko ezinxulumeneyo kwaye ukhethe imizekelo kwizicelo ze-AI ezipapashiweyo.Izinto zokucwangcisa zibandakanyiwe kuphela xa zijongwa njengezifanelekileyo ekuboneleleni ngokusebenza kweklinikhi kwixesha elizayo, njengendlela yokuvavanya iimodeli ukufumanisa ukuba zikulungele na ukusetyenziswa kwizilingo zeklinikhi.Le mizekelo ifikelela incopho kwisicelo esipheleleyo sokuphela-kwisiphelo esichaza amathumba njengento enobungozi okanye enobungozi ngokusekelwe kwimilinganiselo yemifanekiso yezonyango.
Ukungafani kolwazi lwangaphambili.Abathathi-nxaxheba bethu bohluka kwinqanaba labo lolwazi lwemathematika.Umzekelo, abafundi abanemvelaphi yobunjineli ephucukileyo bafuna imathiriyeli enzulu ngakumbi, efana nendlela yokwenza ezabo iinguqu zeFourier.Nangona kunjalo, ukuxoxa nge-algorithm ye-Fourier eklasini ayinakwenzeka kuba ifuna ulwazi olunzulu lokusetyenzwa komqondiso.
Ukuphuma kokuzimasa.Ukuya kwiintlanganiso ezilandelwayo kunqabile, ngakumbi kwiifomathi ze-intanethi.Isisombululo sinokuba kukulandelela ukubakho kunye nokubonelela ngesatifikethi sokugqitywa.Izikolo zonyango zaziwa ngokuqaphela imibhalo yemisebenzi yangaphandle yabafundi, enokukhuthaza abafundi ukuba bafunde isidanga.
Uyilo lweSifundo: Kuba i-AI ivula amabalana amaninzi, ukukhetha iikhonsepthi ezingundoqo zobunzulu obufanelekileyo kunye nobubanzi kunokuba ngumngeni.Ngokomzekelo, ukuqhubeka kokusetyenziswa kwezixhobo ze-AI ukusuka kwibhubhoratri ukuya kwiklinikhi kuyisihloko esibalulekileyo.Ngelixa sigubungela ukucutshungulwa kwangaphambili kwedatha, ukwakhiwa kwemodeli, kunye nokuqinisekiswa, asibandakanyi izihloko ezifana nohlalutyo lwedatha enkulu, ukubonwa okusebenzisanayo, okanye ukuqhuba iimvavanyo zeklinikhi ze-AI, endaweni yoko sigxininisa kwiingcamango ze-AI ezikhethekileyo.Umgaqo wethu osisikhokelo kukuphucula ukufunda nokubhala, hayi izakhono.Ngokomzekelo, ukuqonda indlela imodeli eqhuba ngayo iimpawu zegalelo kubalulekile ekutolikeni.Enye indlela yokwenza oku kukusebenzisa iimephu zokuvula i-gradient, ezinokubona ukuba yeyiphi imimandla yedatha eqikelelwayo.Nangona kunjalo, oku kufuna i-calculus ye-multivariate kwaye ayikwazi ukuqaliswa8.Ukuqulunqa isigama esiqhelekileyo kwakungumngeni kuba sasizama ukucacisa indlela yokusebenza ngedatha njengee-vectors ngaphandle kwe-formalism yezibalo.Qaphela ukuba amagama ahlukeneyo anentsingiselo efanayo, umzekelo, kwi-epidemiology, "uphawu" luchazwa "njengokuguquguquka" okanye "uphawu."
Ukugcinwa kolwazi.Ngenxa yokuba ukusetyenziswa kwe-AI kulinganiselwe, ubungakanani bokuba abathathi-nxaxheba bagcine ulwazi luhlala lubonakala.Ikharityhulamu yesikolo sezonyango ihlala ixhomekeke kuphindaphindo olucwangcisiweyo ukomeleza ulwazi ngexesha lojikelezo olusebenzayo,9 olunokuthi lusetyenziswe kwimfundo ye-AI.
Ubungcali bubaluleke ngaphezu kokwazi ukufunda nokubhala.Ubunzulu bezinto eziphathekayo buyilwe ngaphandle kokuqina kwezibalo, okwakuyingxaki xa kuqalwa izifundo zeklinikhi kubukrelekrele bokwenziwa.Kwimizekelo yenkqubo, sisebenzisa inkqubo yetemplate evumela abathathi-nxaxheba ukuba bazalise imimandla kwaye baqhube isofthiwe ngaphandle kokuqonda indlela yokuseta indawo epheleleyo yeprogram.
Iinkxalabo malunga nobukrelekrele bokwenziwa bujongwane: Kukho inkxalabo exhaphakileyo yokuba ubukrelekrele bokwenziwa bunokungena endaweni yeminye imisebenzi yezonyango3.Ukujongana nalo mbandela, sichaza imida ye-AI, kubandakanywa nenyaniso yokuba phantse zonke iiteknoloji ze-AI ezivunywe ngabalawuli zifuna ukulawulwa kogqirha11.Sikwagxininise ukubaluleka kwe-bias kuba i-algorithms ithande ukuthambekela, ngakumbi ukuba isethi yedatha ayihlukanga12.Ngenxa yoko, iqelana elithile linokwenziwa ngendlela engeyiyo, nto leyo ekhokelela kwizigqibo zeklinikhi ezingalunganga.
Izixhobo ziyafumaneka kuwonke-wonke: Senze izixhobo ezifumanekayo esidlangalaleni, kubandakanywa izilayidi zezifundo kunye nekhowudi.Nangona ukufikelela kumxholo we-synchronous kunqunyelwe ngenxa yeendawo zexesha, umxholo womthombo ovulekileyo yindlela efanelekileyo yokufunda i-asynchronous ekubeni ubuchule be-AI bungafumaneki kuzo zonke izikolo zonyango.
INtsebenziswano yeeDisciplinary Disciplinary: Le workshop yindibaniselwano eqalwe ngabafundi bezonyango ukucwangcisa izifundo kunye neenjineli.Oku kubonisa amathuba entsebenziswano kunye nezikhewu zolwazi kuzo zombini iinkalo, okuvumela abathathi-nxaxheba ukuba baqonde indima enokuba negalelo elinokuba negalelo kwixesha elizayo.
Chaza ubuchule obuphambili be-AI.Ukuchaza uluhlu lwezakhono kubonelela ngesakhiwo esisemgangathweni esinokudityaniswa kwiikharityhulam zonyango ezisekelwe kubuchule obukhoyo.Le workshop njengangoku isebenzisa amaNqanaba eNjongo yesi-2 yesiFundo (Yokuqonda), 3 (iSicelo), kunye nesi-4 (uHlahlelo) lweTaxonomy kaBloom.Ukuba nezibonelelo kumanqanaba aphezulu okuhlela, afana nokwenza iiprojekthi, kunokomeleza ngakumbi ulwazi.Oku kufuna ukusebenzisana neengcali zeklinikhi ukugqiba ukuba izihloko ze-AI zingasetyenziswa njani ekuhambeni komsebenzi weklinikhi kunye nokuthintela ukufundiswa kwezihloko eziphindaphindiweyo esele zibandakanyiwe kwiikharityhulam zonyango eziqhelekileyo.
Yenza izifundo zemizekelo usebenzisa i-AI.Ngokufana nemizekelo yeklinikhi, ukufunda okusekelwe kwimeko kunokomeleza iikhonsepthi ezingabonakaliyo ngokuqaqambisa ukubaluleka kwazo kwimibuzo yeklinikhi.Ngokomzekelo, uphando oluthile lweworkshop luhlalutye i-Google ye-AI-based based diabetic retinopathy inkqubo yokufumanisa i-13 ukuchonga imingeni ecaleni kwendlela esuka kwilebhu ukuya kwikliniki, njengeemfuno zokuqinisekisa zangaphandle kunye neendlela zokulawula imvume.
Sebenzisa amava okufunda: Izakhono zobugcisa zifuna ukuziqhelanisa okugxilwe kunye nokuphindaphinda ukusetyenziswa kwenkosi, efana namava okufunda ajikelezayo abaqeqeshwayo beklinikhi.Esinye isisombululo esinokubakho yimodeli yeklasi ejingisiweyo, ekuye kwanikelwa ingxelo ngayo ukuba iphucule ukugcinwa kolwazi kwimfundo yobunjineli14.Kule modeli, abafundi baphonononga imathiriyeli yethiyori ngokuzimeleyo kwaye ixesha leklasi linikezelwe ekusombululeni iingxaki ngezifundo.
Ukwandiswa kwabathathi-nxaxheba kwiinkalo ezininzi: Sinombono wokwamkelwa kwe-AI okubandakanya intsebenziswano kwiinkalo ezininzi, kubandakanywa oogqirha kunye neengcali zempilo ezihlangeneyo kunye namanqanaba ahlukeneyo oqeqesho.Ke ngoko, ikharityhulamu inokufuna ukuphuhliswa ngokubonisana ne-faculty evela kumasebe ahlukeneyo ukuze ilungelelanise umxholo wabo kwiindawo ezahlukeneyo zokhathalelo lwempilo.
Ubukrelekrele bokwenziwa bubuchwephesha obuphezulu kwaye iikhonsepthi zayo ezingundoqo zinxulumene nemathematika kunye nesayensi yekhompyuter.Ukuqeqesha abasebenzi bezempilo ukuba baqonde ubukrelekrele bokwenziwa buzisa imingeni ekhethekileyo ekukhetheni umxholo, ukufaneleka kweklinikhi, kunye neendlela zokuhambisa.Siyathemba ukuba ulwazi olufunyenwe kwiindibano zocweyo ze-AI kwizeMfundo ziya kunceda abafundisi-ntsapho bexesha elizayo bamkele iindlela ezintsha zokudibanisa i-AI kwimfundo yezonyango.
Iskripthi sePython ye-Google Collaboratory singumthombo ovulekileyo kwaye siyafumaneka: https://github.com/ubcaimed/ubcaimed.github.io/tree/master/.
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Ababhali babulela uDanielle Walker, uTim Salcudin, kunye noPeter Zandstra abavela kwi-Biomedical Imaging kunye ne-Artificial Intelligence Research Cluster kwiYunivesithi yaseBritish Columbia ngenkxaso kunye nenkxaso-mali.
I-RH, PP, ZH, RS kunye ne-MA babenoxanduva lokuphuhlisa umxholo wokufundisa kumasifundisane.I-RH kunye ne-PP babenoxanduva lokuphuhlisa imizekelo yeprogram.I-KYF, i-OY, i-MT kunye ne-PW yayinoxanduva lolungiselelo lolungiselelo lweprojekthi kunye nohlalutyo lweendibano zocweyo.I-RH, i-OY, i-MT, i-RS yayijongene nokudala amanani kunye neetafile.I-RH, KYF, PP, ZH, OY, MY, PW, TL, MA, RS yayinoxanduva lokuyila nokuhlela uxwebhu.
Unxibelelwano lweMedicine lubulela uCarolyn McGregor, uFabio Moraes, kunye no-Aditya Borakati ngegalelo labo ekuhlolweni kwalo msebenzi.
Ixesha lokuposa: Feb-19-2024