INTEGRATSIYALASHGAN BIOKIMYOVIY FENOTIPLASH ASOSIDA ENDOKRIN METABOLIK HOLATLARNI SUN'IY INTELLEKT YORDAMIDA ANIQLASH
DOI:
https://doi.org/10.5281/zenodo.18126378Keywords:
Biokimyoviy fenotiplash, endokrin tizim, metabolik holatlar, sun’iy intellekt, biomarkerlar, mashinaviy o‘rganish.Abstract
Zamonaviy tibbiyotda endokrin va metabolik kasalliklar, jumladan qandli diabet, metabolik sindrom, semirish hamda qalqonsimon bez patologiyalari global sog‘liqni saqlash tizimi oldida turgan eng dolzarb muammolardan biri hisoblanadi. Ushbu kasalliklarning patogenezi murakkab bo‘lib, ko‘plab biokimyoviy, gormonal va genetik omillarning o‘zaro ta’siri bilan belgilanadi. An’anaviy diagnostika usullari ko‘pincha kasallikni kech bosqichlarda aniqlashga olib keladi, bu esa davolash samaradorligini pasaytiradi.
References
Topol, E. J. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. https://doi.org/10.1038/s41591-018-0300-7
Deo, R. C. (2015). Machine learning in medicine. Circulation, 132(20), 1920–1930. https://doi.org/10.1161/CIRCULATIONAHA.115.001593
Libbrecht, M. W., & Noble, W. S. (2015). Machine learning applications in genetics and genomics. Nature Reviews Genetics, 16(6), 321–332. https://doi.org/10.1038/nrg3920
Nicholson, J. K., Lindon, J. C., & Holmes, E. (1999). Metabonomics: Understanding the metabolic responses of living systems to pathophysiological stimuli. Xenobiotica, 29(11), 1181–1189. https://doi.org/10.1080/004982599238047
Hasin, Y., Seldin, M., & Lusis, A. (2017). Multi-omics approaches to disease. Genome Biology, 18(1), 83. https://doi.org/10.1186/s13059-017-1215-1
Hood, L., & Friend, S. H. (2011). Predictive, personalized, preventive, participatory (P4) cancer medicine. Nature Reviews Clinical Oncology, 8(3), 184–187. https://doi.org/10.1038/nrclinonc.2010.227
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
Chen, J. H., & Asch, S. M. (2017). Machine learning and prediction in medicine—Beyond the peak of inflated expectations. New England Journal of Medicine, 376(26), 2507–2509. https://doi.org/10.1056/NEJMp1702071
Price, N. D., Magis, A. T., Earls, J. C., Glusman, G., Levy, R., Lausted, C., ... Hood, L. (2017). A wellness study of 108 individuals using personal, dense, dynamic data clouds. Nature Biotechnology, 35(8), 747–756. https://doi.org/10.1038/nbt.3870
10.Patti, M. E., & Corvera, S. (2010). The role of mitochondria in the pathogenesis of type 2 diabetes. Endocrine Reviews, 31(3), 364–395. https://doi.org/10.1210/er.2009-0027