TIBBIYOTDA DATA MINING: KASALLIKLARNI BASHORAT QILISH VA TASHXISLASHDA QO'LLANILISHI
##plugins.themes.bootstrap3.article.sidebar##
##plugins.themes.bootstrap3.article.main##
Abstrak:
Raqamli transformatsiya jarayonida tibbiyot sohasida data mining texnologiyalari muhim rol o‘ynaydi. Ushbu tezisda tibbiy ma‘lumotlarni qazib olish usullari yordamida kasalliklarni bashorat qilish va tashxislash masalalari ko‘rib chiqiladi. Tadqiqotda decision trees, neural networks, clustering va SVM algoritmlari qo‘llanilgan holda UCI Machine Learning Repositorydan olingan Heart Disease UCI va Breast Cancer Wisconsin datasetlari tahlil qilindi. Natijalar shuni ko‘rsatadiki, data mining yordamida kasalliklarning erta aniqlanishi 85-95% aniqlikka erishishi mumkin, bu tibbiy xizmatlar sifatini oshiradi, xarajatlarni kamaytiradi va bemorlar hayotini saqlab qolish imkoniyatini beradi. Tadqiqot raqamli texnologiyalarni tibbiyotda qo‘llash istiqbollarini ochib beradi.
##plugins.themes.bootstrap3.article.details##
##submission.howToCite##:
##submission.citations##:
Gonzalez R.C., Woods R.E. Digital Image Processing. 4th Edition. – Pearson, 2018.
Process mining and data mining applications in the domain of chronic diseases: A systematic review. – Artificial Intelligence in Medicine, 2023.
Clinical data mining: challenges, opportunities, and recommendations for translational medicine. – Journal of Translational Medicine, 2024.
Data mining concepts in healthcare with discussion on prediction of diseases. – IEEE, 2022.
APPLICATION OF DATA MINING IN HEALTH CARE. – ResearchGate, 2024.
Data Mining in Healthcare: Purpose, Benefits, & Applications. – USF Health Online, 2017.
Data Mining in Healthcare: Benefits, Challenges & Examples. – Kodjin, 2023.
Data Mining for Healthcare: Predicting Disease and Enhancing Patient Care. – LinkedIn, 2024.