DOI:
https://doi.org/10.71337/inlibrary.uz.universaljurnal.110749Kalit so‘zlar:
Katta hajmdagi ma’lumotlar sun’iy intellekt kasalliklarni erta aniqlash mashinaviy o‘qitish chuqur o‘qitish tabiiy tilni qayta ishlash tibbiy ma’lumotlar ma’lumotlarni integratsiyalash maxfiylik onkologik kasalliklar yurak-qon tomir kasalliklari nevrologik kasalliklar federativ o‘qitish kvant hisoblash elektron sog‘liqni saqlash yozuvlari tibbiy tasvirlar genomik ma’lumotlar wearable qurilmalar.Annotasiya
Zamonaviy tibbiyotda katta hajmdagi ma’lumotlar (Big Data) va sun’iy
intellekt texnologiyalari kasalliklarni erta aniqlashda muhim ahamiyatga ega bo‘lib bormoqda.
Ushbu maqola katta hajmdagi tibbiy ma’lumotlarni qayta ishlashning asosiy usullari, ularning
afzalliklari, qiyinchiliklari va kelajakdagi imkoniyatlarini atroflicha tahlil qiladi. Ma’lumotlarni
to‘plash, integratsiyalash, tozalash va tahlil qilish jarayonlari, shuningdek, mashinaviy o‘qitish,
chuqur o‘qitish va tabiiy tilni qayta ishlash kabi zamonaviy yondashuvlarning kasalliklarni
aniqlashdagi samaradorligi ko‘rib chiqiladi. Maqolada onkologik, yurak-qon tomir va nevrologik
kasalliklarning erta tashxisida ushbu texnologiyalarning qo‘llanilishi alohida yoritiladi. Shu bilan
birga, ma’lumotlar sifati, maxfiylik va resurslar bilan bog‘liq muammolar tahlil qilinadi.
Tadqiqotda ilg‘or texnologiyalar, xususan, federativ o‘qitish va kvant hisoblashning kelajakdagi
potensiali ta’kidlanadi. Maqola tibbiy ma’lumotlarni qayta ishlashning hozirgi holati va uning
sog‘liqni saqlash sohasidagi inqilobiy ta’sirini yoritishga qaratilgan bo‘lib, shifokorlar,
tadqiqotchilar va texnologlar uchun qimmatli ma’lumotlar taqdim etadi.
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