Abstract: Over the last few years, artificial intelligence in healthcare has transformed everything regarding disease prediction and diagnosis. Artificial intelligence has proven useful in analyzing ...

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Multiple disease prediction such as Diabetes, Heart disease, Kidney disease, Breast cancer, Liver disease, Malaria, and Pneumonia using supervised machine learning and deep learning algorithms.

In the context of global energy shortages, traditional energy sources face issues of limited reserves and high prices. As a result, the importance of energy storage technology is increasingly ...

Objective: To compare the application of the ARIMA model, the Long Short-Term Memory (LSTM) model and the ARIMA-LSTM model in forecasting foodborne disease incidence. Methods: Monthly case data of ...

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EMBL researchers created SDR-seq, a next-generation tool that decodes both DNA and RNA from the same cell. It finally opens access to non-coding regions, where most disease-associated genetic variants ...

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With the widespread application of lithium-ion batteries in electric vehicles and energy storage systems, health monitoring and remaining useful life prediction have become critical components of ...