The researchers tested four machine learning algorithms: Random Forest, XGBoost, LightGBM, and CatBoost. XGBoost was the most effective at identifying high-risk pregnancies.

Researchers developed a two-stage ML model to predict coating degradation by linking environmental factors to physical changes and corrosion. The framework enables more accurate, data-driven ...

Ministry of HFW, Government of India ordered the NIMNS - National Institute of Mental Health and Neuro Sciences, Bengaluru, in alliance with 15 institutions from across India and made a survey on ...

This study highlights the potential of heart rate variability as an early indicator of gestational diabetes, facilitating ...

Machine learning algorithms are computational models that allow computers to acquire knowledge and improve performance on a task by automatically learning patterns and rules from input data provided ...

Objective Long-term azithromycin treatment effectively prevents acute exacerbations of chronic obstructive pulmonary disease ...

Objective We aimed to estimate prevalence and identify determinants of hypertension in adults aged 15–49 years in Tanzania. Design We analysed cross-sectional survey data from the 2022 Tanzania ...

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