KATTA HAJMDAGI MA’LUMOTLARNI TAHLIL QILISH ASOSIDA TIBBIY PROFILAKTIK CHORALARNI KUCHAYTIRISH IMKONIYATLARI
Kalit so‘zlar:
Big data, Profilaktika, Random Forest, Yurak kasalliklari, Diabet, Tibbiy prognozlash, Sog‘liqni saqlash tizimi, Neyron tarmoqlar, Raqamli tibbiyot.Abstrak
Mazkur maqolada tibbiyotda katta hajmdagi ma’lumotlarni tahlil qilish
asosida profilaktik choralarni kuchaytirish imkoniyatlari tahlil etilgan. O‘zbekiston sog‘liqni
saqlash tizimidagi 75 ming bemorning klinik va statistik ma’lumotlari asosida yurak-qon tomir
kasalliklari, diabet va semizlik xavflarini erta aniqlash uchun prognoz modellari ishlab chiqilgan.
Random Forest algoritmi asosida yuqori aniqlikda bashorat qilish imkoniyati mavjudligi
isbotlangan. Tadqiqot natijalari tibbiy profilaktikani shaxsiylashtirish va resurslarni
optimallashtirish imkonini beradi.
References
ANALYSIS OF MODERN METHODS OF TEACHING AND TRAINING STUDENTS OF THE SPECIALTY "INFORMATION SYSTEMS AND TECHNOLOGIES". (2023). International Journal of Advance Scientific Research, 3(11), 174-178. https://doi.org/10.37547/ijasr-03-11-29
Ikromov Khusan Kholmakhamatovich, . (2023). HISTORICAL CONTEXT OF DEVELOPMENT OF INFORMATION SYSTEMS AND DATABASE MANAGEMENT. International Journal of Pedagogics, 3(11), 119–123. https://doi.org/10.37547/ijp/Volume03Issue11-23
Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447–453.
OVQIQ DO‘KONLARIDA BIZNES JARAYONLARINI AVTOMATLASHTIRISH SAMARALI. (2024). Advance Scientific Research xalqaro
jurnali , 5 (12), 279-284. https://doi.org/10.37547/ijasr-04-12-43
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