Idatha yokwenziwa kunye nokubanakho kwayo kukhathalelo lwempilo

Uninzi lwedatha yokhathalelo lwempilo lwehlabathi ayifumaneki kuphela ngenxa yeenkxalabo eziyimfihlo zezigulana, izithintelo zolawulo ezifana ne-HIPAA, kunye nobuntununtunu bedatha enjalo. Nantsi ingcamango yedatha yokwenziwa: idatha eyenziweyo, eyenziweyo emele ngokuthe ngqo zonke iimpawu zeenkcukacha-manani zeseti yedatha yehlabathi lokwenyani. Kubonakala ngathi yinguqu ephambili kwikamva lokhathalelo lwezempilo.

Kweli nqaku, siceba ukuhlolisisa ubunzima bezobugcisa bedatha yokwenziwa, ukusetyenziswa kwayo kukhathalelo lwempilo, indlela enokutshintsha ngayo uphando lwezonyango, ukuxilongwa, kunye nokulawulwa kwezigulane, kunye nobuchwepheshe obenza oku kwenzeke.

Yintoni i-Synthetic Data?

Idatha ye-synthetic ithathwa njengedatha eyenziwe ngokwenziwa ngokuziphatha okufana nedatha yokwenyani. Iindlela ezininzi zisetyenziselwa ukudala idatha yokwenziwa, kubandakanywa imodeli yezibalo, i-algorithms yokufunda koomatshini , kunye ne-Generative Adversarial Networks (GANs). Nangona idatha yokwenziwa ingenalo naluphi na unxibelelwano lokwenyani kwiifayile zezigulane, idatha engaziwa ayinakwakhiwa ukuze ibonelele ngobunzima bemeko yokhathalelo lwempilo lokwenyani.

Iimpawu eziphambili zeDatha yokwenziwa

• Ukunyaniseka : Ilinganisa ngokufanelekileyo ubume kunye nobudlelwane kwiiseti zedatha.
• Ubumfihlo: Njengoko idatha yokwenziwa ayinayo idatha yesigulane yangempela; luphepha naluphi na uqwalaselo lokuba ngasese.

I-Scalability: Idatha ye-synthetic inokuveliswa ngobuninzi, inikezela ngeeseti ezahlukeneyo zoqeqesho lweemodeli ze-AI okanye ukulinganisa okusebenzayo.

Kutheni i-Synthetic Data kukhathalelo lwezeMpilo?

Ukhathalelo lwempilo lugxile kwidatha; izibhedlele, izibonelelo zophando, kunye neenkampani zamachiza zixhomekeke kakhulu kwidatha yesigulane xa usenza izigqibo. Nangona kunjalo, idatha yokhathalelo lwempilo lokwenyani inomda kwimiba emininzi:

• Imithetho yangasese: Apha, i-GDPR kunye ne-HIPAA inciphisa ukusetyenziswa kwemibutho yezempilo kunye nokwabelana ngedatha yesigulane.
• Ukunqongophala kweDatha: Ngamanye amaxesha, iirekhodi zesigulane ziqulethe idatha engaphelelanga okanye iindawo ezingekhoyo, ezinokuthi zikhokelela ekubeni kubekho i-bias kuhlalutyo.
• Ukuqokelelwa kwedatha okuxabisa kakhulu: Ukuqokelela idatha yomgangatho omkhulu kubiza kakhulu.
• Ukufumaneka okulinganiselweyo: Abaphandi, ngakumbi abo bakumaziko amancinci, abanazo iiseti zedatha yezigulane ezahlukeneyo.

Idatha yeSynthetic isombulula loo mingeni, inikezela ngeendlela ezisesikweni, ezinobungakanani, kunye neendleko ezingezinye. Ukongeza, iiseti zedatha ezenziwe ngokwenziwa zingabandakanya ukuguquguquka kwabantu okwahlukeneyo, iimeko ezinqabileyo, kunye nonyango olungaqhelekanga olunokuthi iiseti zedatha zemveli zingamelanga ngokwaneleyo.

Ubuchule bokuvelisa idatha bubandakanya ubuchule bokudala idatha eyenziweyo

Iindlela ezininzi zobuchwephesha obuphezulu zivumela ukuveliswa kwedatha eyenziweyo. Ezona zidumileyo ziquka:

I-GAN: iNethiwekhi ye-Adversarial Network

Ii-GAN ziphakathi kweendlela zokwenziwa kwedatha ezisetyenziswa kwicandelo lezempilo. I-GAN ineenethiwekhi ezimbini: ijenereyitha kunye nomcaluli. Ijenereyitha ivelisa idatha yokwenziwa, kwaye umcaluli uzama ukufumanisa ukuba yinyani okanye yenziwe. Ngokuhamba kwexesha, iphucula ubuchule bomvelisi, ngaloo ndlela ibonelela ngedatha esemgangathweni wokwenyani.

Ii-GAN zinokufunda kwiiseti zedatha yokucinga yezonyango ukuvelisa ii-MRIs zokwenziwa, ii-CT scans, okanye ii-X-rays, umzekelo, ezinokusetyenziswa njengedatha yoqeqesho okanye ukuqinisekiswa kwe-algorithms ethile kwizicelo zokhathalelo lwempilo. Ngaphaya koko, ii-GANs zikwasetyenziselwe ukudibanisa idatha ye-Electronic Health Records (EHR) ngelixa igcina ubudlelwane bezinto eziguquguqukayo zeklinikhi ngaphandle kokuchaza izazisi zesigulana.

Umzekelo: ikhowudi yepython

 # Example of GAN-based synthetic data generation for EHR from keras.models import Sequential from keras.layers import Dense, LeakyReLU def build_generator(latent_dim): model = Sequential() model.add(Dense(256, input_dim=latent_dim)) model.add(LeakyReLU(alpha=0.2)) model.add(Dense(512)) model.add(LeakyReLU(alpha=0.2)) model.add(Dense(1024)) model.add(LeakyReLU(alpha=0.2)) model.add(Dense(784, activation='sigmoid')) return model

Le khowudi yi-generator elula yemodeli ye-GAN eyenza i-synthetic data modeling data datacareer.

Iikhowudi zokuNgena ngokuzenzekelayo (VAEs)

I-VAE yenye imodeli evelisayo yokwenziwa kwedatha yezempilo eyenziweyo. Ii-VAEs zifakela idata yokwenyani kwisithuba esifihlakeleyo. Ukusuka kule ndawo ifihlakeleyo, iingongoma ezintsha zedatha zenziwe, zigcina iimpawu zeenkcukacha-manani zeseti yedatha yokuqala. Iimodeli ezinjalo zisebenza ngokukodwa ekuveliseni iiseti zedatha ezinomgangatho ophezulu kukhathalelo lwempilo, njenge-genomics okanye i-omics datasets.

IiNethiwekhi zaseBayesi

Uthungelwano lwaseBayesi yimizekelo yemizobo emele ubudlelwane obunokwenzeka phakathi kwezinto ezahlukeneyo. Kukhathalelo lwempilo, olu nxibelelwano lunokuba luncedo ngakumbi ekuveliseni idatha eyenziweyo ebonisa ubudlelwane be-causal, njengekhosi yesifo okanye iziphumo zerejimeni yonyango.

Usetyenziso lweDatha yeSynthetic kukhathalelo lwezeMpilo

Imifanekiso yezoNyango

Idatha ye-Synthetic iguqule umfanekiso wezonyango ngokubonelela ngomsebenzi wokufumaneka okulinganiselweyo kweeseti zedatha ezichazwe ezifunekayo kwiimodeli zokufunda zoomatshini. Kule nkalo, i-GANs kunye ne-VAEs zindlela eziluncedo zokudibanisa i-MRI, i-CT, okanye imifanekiso ye-X-ray. Ukusetyenziswa kwemifanekiso enjalo yokwenziwa kunceda i-radiologists kunye ne-AI algorithms ukuba ibone ukungahambi kakuhle kwi-scan zonyango ngokuchaneka okuphezulu. Idatha yokucinga ye-Synthetic inika abaphandi ithuba lokuqeqesha iimodeli zokufunda nzulu ngaphandle kwemiba yokunqongophala kwedatha okanye ukungcatsha ubumfihlo besigulana.

Umzekelo: Ii-MRIs ezenziwe nge-GAN: Kuvavanyo lwakutsha nje malunga nokwahlulwahlulwa kwethumba lobuchopho, abaphandi basebenzise ii-GAN ukuvelisa imifanekiso eyenziweyo ye-tumor MRI scans. Baye bakwazi ukuqeqesha iimodeli zokufunda ezinzulu ukufumanisa iimeko ezinjalo ngokuchaneka okuphezulu ngaphandle kokufuna umthamo wedatha yesigulane.

Iimvavanyo zeklinikhi

Kusengqondweni ukuba idatha yokwenziwa kufuneka isetyenziswe kunye nedatha yesiqhelo yeklinikhi, kwaye isebenza ngakumbi kwiindawo ezinqabileyo zesifo apho kunzima ukufumana izigulane kwizifundo. I-Synthetic cohorts ivumela umphandi ukuba alinganise iziphumo zesigulane phantsi kweeprothokholi zonyango ezahlukeneyo, ngaloo ndlela kukhawulezisa ukufunyanwa kweziyobisi kunye nokuvavanya.

Umzekelo, ii-EHRs zokwenziwa zinokwenza ukuba iinkampani ezixuba amayeza zilinganise iziphumo zonyango kumaqela athile abaguli. Oku kuya kuvumela uvavanyo lwe-hypothesis kunye nokujonga ukusebenza kwechiza kwaye, okunokwenzeka, ukunciphisa ixesha kunye neendleko zolingo lwezonyango.

Ukwandiswa kweDatha

Idatha ye-Synthetic iya kwenza lula inkqubo yokwandisa idatha ekufundeni koomatshini, ivumela iimodeli ezinamandla zokuqikelela. Iirekhodi zesigulana esizenzileyo okanye idatha yokucinga inokunceda ukongeza iiseti zedatha ezincinci kukhathalelo lwempilo, ukunciphisa ukugqithisa kunye nokuvumela ukwenziwa ngokubanzi kweemodeli ze-AI.

Iyeza elichanekileyo

I-Synthetic genomics, okanye ukuveliswa kwedatha ye-omics, ivula iindlela ezintsha zeyeza elichanekileyo kulo mba. Abaphandi banokuphanda ukuba utshintsho oluthile lwemfuzo luwuchaphazela njani umngcipheko wesifo okanye iimpendulo zonyango ngendlela efanele ukunika unyango olulolwakho ngaphakathi kweeseti zedatha zokwenziwa ezibonisa imfuzo yesigulana.

IiNgqwalaselo zoLawulo neNdlela yokuziphatha

Nangona idatha yokwenziwa inexabiso elininzi, ibonisa imibuzo ebaluleke kakhulu yolawulo kunye nemigaqo yokuziphatha:

Izikhokelo zoLawulo: Abalawuli bezempilo basazama ukuqonda indlela yokuhlela idatha yokwenziwa. Ngenxa yokuba loo datha ayiphumi kwizigulane zokwenyani, inokuba ngaphaya kwemimiselo ekhoyo okanye ngaphandle kwendawo yolawulo lwee-arhente ezilawulayo. Nangona kunjalo, kufuneka ihambelane neemfuno zokuziphatha kusetyenziso lwezempilo lwe-AI.

I-Bias yokuveliswa kwedatha: Nayiphi na imodeli yokwenziwa kwedatha inomkhethe okanye iziphene. Oku kunokwenza ukuba i-dataset enesiphumo ibonise ukungafezeki okunjalo kwaye kubangele iziphumo zophando eziphosakeleyo okanye ezicalucalulo okanye uqikelelo olungalunganga lwe-AI.

Ukuqinisekiswa: Idatha ye-Synthetic kufuneka iqinisekiswe ukunyaniseka kunye nokunyaniseka. Kungenxa yokuba idatha eyenziweyo inokubonisa idatha yokwenyani, ayiyenzi ilunge ngokwaneleyo kwizicelo zokhathalelo lwempilo oluthatha ixesha.

Ezinye zezixhobo eziphambili kunye nesakhelo esandula ukuvela ukuxhasa ukwenziwa kwedatha yezempilo eyenziweyo zezi zilandelayo:

I-CTGAN: Isishunqulelo se-Conditional Tabular GAN, isixhobo esivulelekileyo sokuvelisa idatha yetheyibhile yokwenziwa. Iqhele ukuphunyezwa kukhathalelo lwempilo ukudibanisa ii-EHRs.

I-Synthpop : Esi sisixhobo se-R sokuvelisa iinguqulelo ezenziweyo zedatha ebuthathaka. Isetyenziswe ngokubanzi ukuvelisa iiseti zedatha ezigcina ubumfihlo kukhathalelo lwempilo.

I-Synthesizer yeDatha: UMthombo oVulelekileyo we-Synthesizer Uvelisa iiSeti zedatha zokwenziwa ngoBucala buGciniwe. Isixhobo sixhasa iimodeli zeMowudi yeSiphawulo esiHlangeneyo, esiZimeleyo, kunye neNxulunyanisiweyo.

Ukukrotyiswa kweKamva leDatha yeSynthetic kukhathalelo lwezeMpilo

Idatha ye-Synthetic inamandla amakhulu kukhathalelo lwempilo. I-AI ephuculweyo kunye neemodeli ezivelisayo zinokukhawulezisa kakhulu ukuqamba izinto ezintsha kwiindawo ezimbalwa:

I-Telemedicine: Ngombono okhulayo we-telemedicine, kunokwenzeka ukuba uyile i-synthetic data-based training datasets kwiinkqubo ze-AI ezibandakanyekayo ekubekweni kweliso kwesigulane kunye nokuxilongwa.

I-AI kwi-Diagnostics: Uqeqesho kwiinkcukacha zokwenziwa ezilinganisa iimeko ezinqabileyo okanye ezingabonakaliswa ngaphantsi kunokunyusa ukuchaneka kokuxilongwa kwezifo kwizigulane ngeenkqubo zokunakekelwa kwempilo, ngakumbi kwizifo ezinqabileyo.

**UPhando oluDibeneyo lweZiko:**Idatha enziweyo inokuqinisekisa ukwabelana ngokukhuselekileyo kwedatha yezempilo kuwo onke amaziko. Oku kunceda intsebenziswano yehlabathi ngaphandle kokongeza nayiphi na imiba enxulumene nobumfihlo.

Ukuqukumbela

Idatha ye-Synthetic imele utshintsho lweparadigm kukhathalelo lwempilo kuba ivumela idatha ukuba igqithe iziphene zayo ezinokubakho ekufikeleleni, ukulinganisa, kunye nemiba yabucala. Abaphandi, oogqirha, kunye nabaphuhlisi be-AI baya kukhululeka ukuba bavelise izinto ezintsha ngaphandle kokubeka esichengeni ubumfihlo besigulane okanye imilinganiselo yokuziphatha. Ngokuqhubekayo ngokutsha kwiimodeli ezivelisayo, kubandakanywa ii-GAN, ii-VAEs, kunye neenethiwekhi ze-Bayesian, idatha yokwenziwa iya kuba sisixhobo ekubumbeni ikamva lokhathalelo lwempilo, ukusuka kwizilingo zeklinikhi kunye nokuxilongwa ukuya kwiyeza lomntu.

Ngokusebenzisa ngobunono obu buchwephesha, icandelo lezempilo linokuthi livule amathuba angazange abonwe ngaphambili kukhathalelo lwesigulana, uphando kunye nokusungula izinto ezintsha.