labarai

Tun lokacin da IBM Watson ya fara a cikin 2007, mutane suna ci gaba da bin ci gaban ilimin likitanci (AI). Tsarin AI mai amfani kuma mai ƙarfi na likitanci yana da babbar dama don sake fasalin kowane fanni na likitancin zamani, yana ba da damar mafi wayo, mafi inganci, inganci, da kulawa mai haɗa kai, yana kawo jin daɗi ga ma'aikatan kiwon lafiya da marasa lafiya, kuma ta haka inganta lafiyar ɗan adam. A cikin shekaru 16 da suka gabata, kodayake masu binciken AI na likitanci sun taru a cikin ƙananan fannoni daban-daban, a wannan matakin, har yanzu ba su iya kawo almarar kimiyya ga gaskiya ba.

A wannan shekara, tare da ci gaban juyin juya halin fasahar AI kamar ChatGPT, AI na likitanci ya sami babban ci gaba a fannoni da yawa. Nasarar da ba a taɓa ganin irin ta ba a cikin ikon AI na likitanci: Mujallar yanayi ta ci gaba da ƙaddamar da binciken babban samfurin harshe na likitanci da samfurin asali na hoton likita; Google ya saki Med-PaLM da magajinsa, ya kai matakin ƙwararru a cikin tambayoyin gwajin Likitan Likitan Amurka. Manyan mujallu na ilimi za su mai da hankali kan AI na likitanci: Yanayin yana fitar da ra'ayi akan ainihin samfurin AI na likitanci na gabaɗaya; Bayan jerin sake dubawa na AI a cikin Magunguna a farkon wannan shekara, Jaridar New England Journal of Medicine (NEJM) ta buga nazarin lafiyar lafiyar dijital ta farko a ranar 30 ga Nuwamba, kuma ta kaddamar da fitowar farko ta NEJM sub-journal NEJM AI a kan Disamba 12. Likita AI saukowa ƙasa ya kara girma: JAMA sub-jarida buga da duniya likita image sharing yunƙurin; Hukumar Abinci da Magunguna ta Amurka (FDA) tana haɓaka daftarin ƙa'idodi don ƙa'idodin AI na likita.

A ƙasa, mun sake nazarin gagarumin ci gaban da masu bincike a duk duniya suka samu ta hanyar amfani da AI a cikin 2023.

Medical AI Basic Model

Gina samfurin asali na AI na likita ba shakka shine mafi kyawun binciken bincike na wannan shekara. Mujallun Nature sun buga labarin bita kan tsarin kula da lafiya na duniya na duniya da babban tsarin harshe na kiwon lafiya a cikin shekara. Likita Image Analysis, babban jarida a cikin masana'antu, bita da kuma sa ido ga kalubale da dama na asali model bincike a likita image bincike, da kuma gabatar da manufar "tushen asali model" don taƙaitawa da kuma jagorantar ci gaban asali model bincike na likita AI. Makomar ainihin ƙirar AI don kiwon lafiya tana ƙara bayyana. Yin la'akari da misalan nasara na manyan nau'ikan harshe irin su ChatGPT, ta yin amfani da ƙarin hanyoyin kulawa da kai kafin horo da kuma tarin bayanan horo, masu bincike a fannin likitanci AI suna ƙoƙarin gina 1) takamaiman nau'ikan tushe na cuta, 2) samfuran tushe na yau da kullun, da 3) manyan samfuran multimodal waɗanda ke haɗa nau'ikan ma'auni masu yawa da iyakoki masu yawa tare da ma'auni masu yawa tare da ma'auni mai girma

Samfuran Bayanan Likitan AI

Baya ga manyan nau'ikan AI waɗanda ke taka rawa sosai a cikin ayyukan bincike na bayanan asibiti na ƙasa, a cikin siyan bayanan asibiti na sama, fasahar da ke wakiltar samfuran AI ta haɓaka ta kuma fito. Tsarin, saurin, da ingancin sayan bayanai na iya haɓakawa sosai ta hanyar AI algorithms.

A farkon wannan shekara, Nature Biomedical Engineering ya buga wani bincike daga Jami'ar Straits ta Turkiyya wanda ya mayar da hankali kan yin amfani da AI don magance matsalar cututtukan cututtukan cututtukan cututtukan cututtukan cututtukan fata a aikace-aikacen asibiti. Abubuwan da ke cikin sassan sassan daskararre yayin tiyata sune cikas ga saurin tantancewa. Kodayake nama na formalin da paraffin da aka saka (FFPE) suna ba da samfurin inganci mafi girma, tsarin samar da shi yana ɗaukar lokaci kuma yana ɗaukar sa'o'i 12-48, yana sa shi rashin dacewa don amfani da tiyata. Saboda haka ƙungiyar binciken ta ba da shawarar wani algorithm da ake kira AI-FFPE, wanda zai iya yin bayyanar nama a cikin daskararre mai kama da FFPE. Algorithm ya yi nasarar gyara kayan aikin sassan daskararre, ya inganta ingancin hoto, kuma ya riƙe abubuwan da suka dace na asibiti a lokaci guda. A cikin ingantacciyar asibiti, AI-FFPE algorithm yana inganta ingantaccen bincike na ƙwayoyin cuta don ƙananan nau'ikan ƙari, yayin da yake rage lokacin tantancewar asibiti sosai.

Rahoton Magungunan Cell ya ba da rahoton wani aikin bincike na ƙungiyar daga Kwalejin Kiwon Lafiya ta Uku na Jami'ar Jilin, Sashen Nazarin Radiyo, Asibitin Zhongshan mai alaƙa da Jami'ar Fudan, da Jami'ar Kimiyya da Fasaha ta Shanghai [25]. Wannan binciken yana ba da shawarar babban maƙasudi mai zurfi na ilmantarwa da tsarin haɗin gwiwar sake ginawa (Hybrid DL-IR) tare da haɓaka mai yawa da sassauci, yana nuna kyakkyawan aikin sake gina hoto a cikin sauri MRI, ƙananan CT, da sauri PET. Algorithm na iya cimma MR Single-organ multi-sequence scanning a cikin dakika 100, rage adadin radiation zuwa 10% kawai na hoton CT, kuma ya kawar da hayaniya, kuma zai iya sake gina ƙananan raunuka daga sayen PET tare da haɓakawa sau 2 zuwa 4, yayin da rage tasirin kayan aikin motsi.

Likita AI a Haɗin gwiwa tare da Ma'aikatan Lafiya

Haɓaka haɓakar haɓakar likitancin AI kuma ya haifar da ƙwararrun likitocin suyi la'akari da gaske da kuma bincika yadda ake haɗin gwiwa tare da AI don haɓaka hanyoyin asibiti. A cikin Yuli na wannan shekara, DeepMind da ƙungiyar masu bincike da yawa sun ba da shawarar tsarin AI mai suna Complementary Driven Clinical Workflow Delay (CoDoC) . An fara gano tsarin bincike ta hanyar tsarin AI mai tsinkaya, sannan aka yi hukunci da wani tsarin AI akan sakamakon da ya gabata, kuma idan akwai shakka, an gano cutar ta ƙarshe ta hanyar likita don inganta daidaiton ganewar asali da daidaitattun daidaito. Idan ya zo ga gwajin cutar kansar nono, CoDoC ya rage ƙimar gaskiya ta 25% tare da ƙimar ƙarancin ƙarya iri ɗaya, yayin da rage yawan aikin likitocin da kashi 66%, idan aka kwatanta da tsarin sasantawa biyu na yanzu a Burtaniya. Dangane da rarrabuwa na tarin fuka, an rage ƙimar tabbataccen ƙarya da kashi 5 zuwa 15 tare da ƙimar ƙarancin ƙarya iri ɗaya idan aka kwatanta da AI mai zaman kanta da ayyukan aiki na asibiti.

Hakazalika, Annie Y. Ng et al., na Kamfanin Kheiron a London, Birtaniya, ya gabatar da ƙarin masu karatu AI (tare da haɗin gwiwar masu binciken ɗan adam) don sake nazarin sakamakon lokacin da babu sakamakon tunawa a cikin tsarin sasantawa na karantawa sau biyu, wanda ya inganta matsalar ganowa da aka rasa a farkon binciken ciwon nono, kuma tsarin ba shi da kusan wani sakamako na ƙarya . Wani binciken, wanda ƙungiyar ta jagoranci a Makarantar Kiwon Lafiya ta Jami'ar Texas McGovern kuma ta kammala a cibiyoyin bugun jini guda huɗu, ta yi amfani da fasahar AI mai ƙididdige ƙididdiga ta angiography (CTA) don sarrafa sarrafa gano manyan bugun jini na ischemic bugun jini (LVO). Ma'aikatan asibiti da masu aikin rediyo suna karɓar faɗakarwa na ainihin-lokaci akan wayoyin hannu a cikin mintuna kaɗan da kammala hoton CT, suna sanar da su yiwuwar kasancewar LVO. Wannan tsarin AI yana inganta ayyukan aiki a cikin asibiti don mummunan bugun jini na ischemic, yana rage lokacin ƙofa zuwa-kwakwalwa daga shigar da jiyya da kuma ba da damar samun nasarar ceto. An buga sakamakon binciken a cikin JAMA Neurology.

Samfurin Kiwon Lafiya na AI don Amfanin Duniya

2023 kuma za ta ga kyawawan ayyuka masu yawa waɗanda ke amfani da AI na likitanci don nemo abubuwan da ba a iya gani ga idon ɗan adam daga ƙarin bayanan da ake iya samu, yana ba da damar ganewar asali na duniya da fara tantancewa a sikelin. A farkon wannan shekara, likitancin yanayi ya buga nazarin binciken da Cibiyar Ido ta Zhongshan ta Jami'ar Sun Yat-sen da Asibitin Hade na Biyu na Jami'ar Kiwon Lafiya ta Fujian suka yi. Yin amfani da wayoyin hannu a matsayin tashoshin aikace-aikacen, sun yi amfani da hotuna masu kama da zane na bidiyo don jawo hankalin yara da rikodin halayen kallon yara da yanayin fuska, kuma sun kara yin nazari na rashin daidaituwa ta hanyar amfani da tsarin ilmantarwa mai zurfi don samun nasarar gano cututtukan ido 16, ciki har da cataracts, na haihuwa ptosis da glaucoma na haihuwa, tare da matsakaicin daidaiton tantancewa fiye da 85%. Wannan yana ba da ingantacciyar hanya kuma mai sauƙi don faɗaɗa hanyoyin fasaha don babban gwajin farko na rashin aikin gani na jarirai da cututtukan ido masu alaƙa.

A karshen wannan shekara, likitancin dabi'a ya ba da rahoton wani aikin da cibiyoyin kiwon lafiya da bincike sama da 10 suka yi a duniya, ciki har da Cibiyar Kula da Cututtuka ta Shanghai da Asibitin Farko na Jami'ar Zhejiang. Marubucin ya yi amfani da AI don gwajin cutar kansa na pancreatic na mutanen da ke fama da asymptomatic a cibiyoyin gwajin jiki, asibitoci, da dai sauransu, don gano fasalin raunin a cikin hotunan CT na zahiri waɗanda ke da wahalar ganowa da ido tsirara kawai, ta yadda za a iya samun ingantaccen kuma ba mai saurin kamuwa da cutar kansar pancreatic da wuri. A cikin nazarin bayanai daga fiye da marasa lafiya 20,000, samfurin ya kuma gano lokuta 31 na raunin da aka rasa a asibiti, wanda ya inganta sakamakon asibiti.

Raba bayanan Likita

A cikin 2023, yawancin ingantattun hanyoyin musayar bayanai da kuma shari'o'in nasara sun bayyana a duniya, suna tabbatar da haɗin gwiwa tsakanin cibiyoyi da yawa da buɗe bayanai a ƙarƙashin tushen kare sirrin bayanai da tsaro.

Na farko, tare da taimakon fasahar AI kanta, masu bincike na AI sun ba da gudummawa ga rarraba bayanan likita. Qi Chang da wasu daga Jami'ar Rutgers a Amurka sun buga wata kasida a cikin Sadarwar yanayi, suna ba da shawarar tsarin ilmantarwa na tarayya na DSL dangane da hanyoyin sadarwar abokan gaba da aka rarraba, wanda ke amfani da AI don horar da takamaiman bayanan da aka samar na cibiyoyi masu yawa, sa'an nan kuma ya maye gurbin ainihin bayanan cibiyoyin da yawa tare da bayanan da aka samar. Tabbatar da horarwar AI bisa manyan bayanai masu yawa yayin da ake kare sirrin bayanai. Ƙungiyar guda kuma ta buɗe tushen bayanan da aka samar da hotuna da kuma bayanan da suka dace. Samfurin rarrabuwa da aka horar akan saitin bayanan da aka samar zai iya cimma irin wannan sakamako ga ainihin bayanan.

Tawagar Dai Qionghai daga Jami'ar Tsinghua ta buga takarda kan npj Digital Health, tana ba da shawarar Relay Learning, wanda ke amfani da manyan bayanai masu yawa don horar da samfuran AI a ƙarƙashin tushen ikon bayanan gida kuma babu haɗin yanar gizo. Yana daidaita bayanan tsaro da damuwa na sirri tare da neman aikin AI. Wannan tawagar daga baya tare da haɓaka da kuma tabbatar da CAIMEN, tsarin ƙirjin ƙirjin CT pan-mediastinal tumor ganewar ƙwayar cuta wanda ya dogara da ilimin tarayya, tare da haɗin gwiwar Asibitin Farko na Jami'ar Kiwon Lafiyar Guangzhou da asibitoci 24 a duk faɗin ƙasar. Tsarin, wanda za'a iya amfani da shi ga ciwace-ciwacen daji na yau da kullun na 12, ya sami kashi 44.9 cikin 100 mafi inganci idan aka yi amfani da shi kaɗai fiye da lokacin da ƙwararrun ɗan adam suka yi amfani da shi kaɗai, kuma kashi 19 cikin ɗari mafi kyawun ganewar asali lokacin da masana ɗan adam suka taimaka masa.

A gefe guda, ana kan aiwatar da shirye-shirye da yawa don gina amintattun, na duniya, manyan na'urorin kiwon lafiya. A cikin Nuwamba 2023, Agustina Saenz da sauransu daga Sashen Ilimin Kimiyyar Halittu a Makarantar Kiwon Lafiya ta Harvard sun buga kan layi a Lancet Digital Health tsarin duniya don raba bayanan hoto na likita da ake kira Bayanan Hannun Hannun Artificial don Duk Kiwon Lafiya (MAIDA). Suna aiki tare da ƙungiyoyin kiwon lafiya a duk faɗin duniya don ba da cikakkiyar jagora kan tattara bayanai da kuma ganowa, ta yin amfani da samfur ɗin Abokin Muzaharar Tarayyar Amurka (FDP) don daidaita musayar bayanai. Suna shirin sakin bayanan da aka tattara a hankali a yankuna daban-daban da Saitunan asibiti a duniya. Ana sa ran fitar da bayanan farko a farkon 2024, tare da ƙarin zuwa yayin da haɗin gwiwar ke haɓaka. Aikin wani muhimmin yunƙuri ne na gina ƙaƙƙarfan bayanai na AI na jama'a, mai girma da kuma daban-daban.

Bayan wannan shawara, UK Biobank ya kafa misali. Bankin Biobank na Burtaniya ya fitar da sabbin bayanai a ranar 30 ga Nuwamba daga dukkan jerin kwayoyin halittar mahalarta 500,000. Ma'ajiyar bayanai, wacce ke buga cikakken jerin kwayoyin halittar kowane daga cikin masu aikin sa kai na Biritaniya 500,000, ita ce mafi girman cikakkun bayanan kwayoyin halittar dan adam a duniya. Masu bincike a duk faɗin duniya na iya buƙatar samun damar yin amfani da wannan bayanan da ba a tantance ba kuma su yi amfani da su don bincika tushen tushen lafiya da cututtuka. Bayanan kwayoyin halitta sun kasance suna da matukar mahimmanci don tabbatarwa a baya, kuma wannan nasara mai tarihi na UK Biobank ya tabbatar da cewa yana yiwuwa a gina buɗaɗɗen bayanai, marar sirri na duniya. Tare da wannan fasaha da bayanan bayanai, AI likita ya daure ya shigo da tsalle na gaba.

Tabbatarwa da Kima na Likita AI

Idan aka kwatanta da saurin ci gaban fasahar AI ta likitanci kanta, haɓakar tabbatarwa da kimantawa na likitancin AI yana ɗan jinkirin. Tabbatarwa da kimantawa a cikin babban filin AI sau da yawa suna watsi da ainihin bukatun likitoci da marasa lafiya don AI. Gwajin gwaje-gwajen asibiti da bazuwar al'ada sun yi matuƙar wahala don dacewa da saurin haɓaka kayan aikin AI. Haɓaka tsarin tabbatarwa da tsarin ƙima wanda ya dace da kayan aikin AI na likitanci da wuri-wuri shine abu mafi mahimmanci don haɓaka AI na likitanci don haɓaka bincike da haɓaka da gaske zuwa saukowa na asibiti.

A cikin takardar bincike na Google akan Med-PaLM, wanda aka buga a cikin Nature, ƙungiyar ta kuma buga maƙasudin ƙima na MultiMedQA, wanda ake amfani da shi don tantance ikon manyan samfuran harshe don samun ilimin asibiti. Ma'auni ya haɗu da bayanan ƙwararrun ƙwararrun likitocin Q&A guda shida, wanda ke rufe ilimin ƙwararrun likitanci, bincike da sauran fannoni, kazalika da bayanan bayanan tambayoyin likitancin kan layi, la'akari da Q&A na likita-majinyata akan layi, ƙoƙarin horar da AI zuwa ƙwararren likita daga fannoni da yawa. Bugu da ƙari, ƙungiyar ta ba da shawarar tsarin da ya danganci kima na ɗan adam wanda ke yin la'akari da nau'i-nau'i masu yawa na gaskiya, fahimta, tunani, da yiwuwar son zuciya. Wannan shine ɗayan mafi yawan ƙoƙarin bincike na wakilci don kimanta AI a cikin kiwon lafiya da aka buga a wannan shekara.

Koyaya, gaskiyar cewa manyan nau'ikan harshe suna nuna babban matakin ɓoye ilimin asibiti yana nufin cewa manyan nau'ikan harshe sun cancanci ayyukan asibiti na gaske? Kamar dai yadda ɗalibin likitancin da ya ci jarrabawar ƙwararrun likitanci tare da cikakkiyar maƙiyi har yanzu ya yi nisa da babban likitan solo, ƙa'idodin kimantawa da Google ya gabatar na iya zama cikakkiyar amsa ga batun kima AI na likitanci don ƙirar AI. Tun daga farkon 2021 da 2022, masu bincike sun ba da shawarar jagororin bayar da rahoto kamar Decid-AI, SPIRIT-AI, da INTRPRT, suna fatan jagorantar farkon haɓakawa da tabbatar da lafiyar AI a ƙarƙashin yanayin la'akari da dalilai kamar ƙwarewar aikin asibiti, aminci, abubuwan ɗan adam, da nuna gaskiya/fassara. Kwanan nan, Mujallar Nature Medicine ta buga wani binciken da masu bincike daga Jami'ar Oxford da Jami'ar Stanford suka yi kan ko za a yi amfani da "tabbatarwar waje" ko "tabbatar da gida mai maimaitawa. "Don inganta kayan aikin AI.

Halin rashin son kai na kayan aikin AI kuma shine muhimmin jagorar kimantawa wanda ya sami kulawa a wannan shekara daga duka labaran Kimiyya da NEJM. AI sau da yawa yana nuna son zuciya saboda yana iyakance ga bayanan horo. Wannan son zuciya na iya nuna rashin daidaituwar zamantakewa, wanda ke ƙara rikidewa zuwa wariyar algorithmic. Cibiyoyin Lafiya na Ƙasa kwanan nan sun ƙaddamar da shirin Bridge2AI, wanda aka kiyasta zai kashe dala miliyan 130, don gina bayanai daban-daban (daidai da manufofin shirin MAIDA da aka ambata a sama) waɗanda za a iya amfani da su don tabbatar da rashin son zuciya na kayan aikin AI na likita. MultiMedQA ba ya la'akari da waɗannan abubuwan. Tambayar yadda ake aunawa da tabbatar da samfuran AI na likitanci har yanzu suna buƙatar tattaunawa mai zurfi da zurfi.

A cikin Janairu, Nature Medicine ya buga wani ra'ayi mai suna "Magungunan Bayanai na gaba" daga Vivek Subbiah na Jami'ar Texas MD Anderson Cancer Center, yana nazarin iyakokin gwaje-gwajen asibiti da aka fallasa a cikin mahallin cutar ta COVID-19 tare da nuna sabani tsakanin sabbin abubuwa da kuma bin tsarin binciken asibiti. A ƙarshe, yana nuna makomar sake fasalin gwaje-gwaje na asibiti - ƙarni na gaba na gwaji na asibiti ta amfani da hankali na wucin gadi, wato, yin amfani da hankali na wucin gadi daga adadi mai yawa na bayanan bincike na tarihi, bayanan duniya na ainihi, bayanan asibiti da yawa, bayanan na'urar da za a iya amfani da su don samun shaida mai mahimmanci. Shin wannan yana nufin cewa fasahar AI da hanyoyin tabbatar da asibiti na AI na iya ƙarfafa juna da haɓakawa a nan gaba? Wannan ita ce buɗaɗɗiyar tambaya mai jan hankali ta 2023.

Dokokin Medical AI

Ci gaban fasahar AI kuma yana haifar da ƙalubale ga ƙa'idodin AI, kuma masu tsara manufofi a duniya suna ba da amsa a hankali da hankali. A cikin 2019, FDA ta fara buga Tsarin Tsarin Mulki don Canje-canjen Software zuwa Na'urorin Likitan Ingantattun Hannun Hannu (Tattaunawar Tattaunawa), yana ba da cikakken bayani game da yuwuwar hanyarta ta bita na farko na AI da gyare-gyaren software na koyo. A cikin 2021, FDA ta ba da shawarar "Tsarin Hankali na Artificial/Tsarin Ilimin Injiniya azaman Tsarin Ayyukan Na'urar Kiwon Lafiya", wanda ya fayyace ƙayyadaddun ƙayyadaddun matakan ka'idojin likitancin AI guda biyar. A wannan shekara, FDA ta sake fitar da Gabatarwar Kasuwa don Siffofin Software na Na'ura don samar da bayanai kan shawarwarin ƙaddamar da kasuwa don ƙimar FDA na aminci da ingancin fasalolin software na na'ura, gami da wasu fasalolin na'urar software waɗanda ke amfani da nau'ikan koyan na'ura waɗanda aka horar da su ta hanyoyin koyon injin. Manufar tsarin FDA ta samo asali daga tsari na farko zuwa jagora mai amfani.

Bayan da aka buga sararin Bayanan Kiwon Lafiyar Turai a watan Yulin bara, EU ta sake kafa dokar leƙen asiri ta Artificial. Tsohon yana nufin yin amfani da mafi kyawun bayanan kiwon lafiya don samar da ingantaccen kiwon lafiya, rage rashin daidaito, da kuma bayanan tallafi don rigakafi, ganewar asali, jiyya, ƙididdiga na kimiyya, yanke shawara da dokoki, yayin da tabbatar da cewa 'yan ƙasa na EU suna da iko mafi girma akan bayanan lafiyar su. Ƙarshen ya bayyana a fili cewa tsarin ganewar asibiti babban tsarin AI ne mai haɗari, kuma yana buƙatar ɗaukar kulawa mai karfi da aka yi niyya, kulawar sake zagayowar rayuwa gabaɗaya da kuma sa ido na farko. Hukumar Kula da Magunguna ta Turai (EMA) ta buga Takaddun Tunatarwa na Draft akan amfani da AI don tallafawa haɓakar magunguna, ƙa'ida da amfani, tare da mai da hankali kan haɓaka amincin AI don tabbatar da amincin haƙuri da amincin sakamakon binciken asibiti. Gabaɗaya, tsarin tsarin EU yana ɗaukar tsari sannu a hankali, kuma bayanan aiwatarwa na ƙarshe na iya zama dalla-dalla da tsauri. Ya bambanta da tsattsauran ƙa'idar EU, tsarin tsarin AI na Burtaniya ya bayyana a sarari cewa gwamnati na shirin ɗaukar matakai mai laushi kuma ba za ta ƙaddamar da sabbin kuɗaɗen ba ko kafa sabbin masu gudanarwa a yanzu.

A cikin China, cibiyar karatun fasaha na likita (NMPA) na kayan aikin likitanci na ƙasa ya bayar da takaddun da aka tabbatar da su na kayan aikin software na kayan aikin wucin gadi (A'a. 47 a cikin 2021). A wannan shekara, an sake fitar da "Takaitaccen sakamakon rarrabuwar kayan aikin likita na farko a cikin 2023." Wannan jerin takaddun yana ba da ma'anar, rarrabuwa da ka'idoji na samfuran software na likitanci na wucin gadi da sauƙin aiki, kuma yana ba da cikakken jagora ga matsayi na samfur da dabarun rajista na masana'antu daban-daban a cikin masana'antar. Waɗannan takaddun suna ba da tsari da yanke shawara na gudanarwa don tsarin kimiyya na AIlig na'urorin kiwon lafiya da ke sa ido kan na'urorin kiwon lafiya na China. Taron da aka gudanar a birnin Hangzhou daga ranar 21 zuwa 23 ga watan Disamba ya kafa wani taro na musamman kan harkokin kiwon lafiya na dijital da inganta ingancin asibitocin jama'a da gwajin na'urorin likitanci na wucin gadi da tantance fasahar daidaita masana'antu a wancan lokacin, jami'ai daga hukumar raya kasa da yin kwaskwarima ta kasa da NMPA za su halarci taron kuma za su iya fitar da sabbin bayanai.

Kammalawa

A cikin 2023, AI na likitanci ya fara haɗawa cikin duka tsarin aikin likita na sama da ƙasa, yana rufe tattara bayanan asibiti, haɗuwa, bincike, ganowa da jiyya, da tantancewar al'umma, da haɗin gwiwa ta jiki tare da ma'aikatan kiwon lafiya / cututtuka, suna nuna yuwuwar kawo jin daɗin lafiyar ɗan adam. Binciken likitancin AI mai amfani ya fara wayewa. A nan gaba, ci gaban likitancin AI ba kawai ya dogara da ci gaban fasaha da kansa ba, har ma yana buƙatar cikakken haɗin gwiwar masana'antu, jami'a da bincike na likita da goyon bayan masu tsara manufofi da masu tsarawa. Wannan haɗin gwiwar yanki shine mabuɗin don cimma ayyukan haɗin gwiwar AI, kuma tabbas zai haɓaka haɓakar lafiyar ɗan adam.