
Ushbu maqolada tibbiyot sohasida sun’iy neyron tarmoqlarini qo‘llashning amaliy imkoniyatlari, afzalliklari va cheklovlari o‘rganilgan. Sun’iy neyron tarmoqlari biologik neyron tizimlariga o‘xshash tarzda ishlovchi kompyuter modellaridir. Ular katta hajmdagi tibbiy ma’lumotlarni, jumladan tibbiy tasvirlar, laboratoriya natijalari, genomik ma’lumotlar va bemor kuzatuvlarini tahlil qilish imkonini beradi. Maqolada turli arxitekturalar, xususan konvolyutsion, rekurent va feedforward tarmoqlarning diagnostika, kasalliklarni erta aniqlash va shaxsiylashtirilgan davolashdagi roli ko‘rib chiqilgan. Shuningdek, ma’lumotlarni tayyorlash, o‘rganish algoritmlari, model interpretatsiyasi va klinik qo‘llanilishdagi muammolar muhokama qilingan. Tadqiqot natijalari shuni ko‘rsatadiki, sun’iy neyron tarmoqlari an’anaviy metodlarga qaraganda ko‘proq aniqlik va samaradorlikni ta’minlaydi, bu esa bemorlar sog‘lig‘ini yaxshilash va tibbiy qaror qabul qilishni optimallashtirish imkonini beradi.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
