PREDICTION OF THE INFLUENCE OF WEATHER CONDITIONS ON HEART BLOOD PRESSURE DISEASES BASED ON THE LSTM MODEL
Keywords:
Yurak-qon bosimi kasalliklari, LSTM modeli, ob-havo sharoitlari, chuqur o‘rganish, bashorat qilish tizimlari, profilaktika, sog‘liqni saqlash tizimi.Abstract
Cardiovascular diseases are widespread globally and are one of the leading causes of mortality. This study uses the LSTM (Long Short-Term Memory) deep learning model to predict the impact of weather conditions (temperature, atmospheric pressure, relative humidity, wind speed, and geomagnetic activity) on cardiovascular diseases. The findings demonstrate the model's high accuracy, making it a valuable tool for preventive measures and healthcare. This work lies at the intersection of medicine, meteorology, and artificial intelligence, fostering interdisciplinary collaboration.
References
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Pulatov, G., Kabildjanov, A., & Pulatova, G. (2024). АНАЛИТИЧЕСКИЙ АНАЛИЗ ВЛИЯНИЯ ПОГОДНЫХ УСЛОВИЙ НА СЕРДЕЧНО-СОСУДИСТЫЕ ЗАБОЛЕВАНИЯ. Потомки Аль-Фаргани, 1(2), 296–300.
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Copyright (c) 2024 Giyos Pulatov, Aleksandr Kabildjanov, Gulxayo Pulatova
This work is licensed under a Creative Commons Attribution 4.0 International License.
