Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
Researchers developed a machine-learning-assisted approach to improve micro-electro-discharge machining (µ-EDM) of the ...
New deep-learning framework reconstructs hourly PM2.5 chemical composition using air-quality and meteorological data ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
AI & Society, states that algorithmic systems often construct competing but equally valid “model-worlds,” offering empirical support for a philosophical claim that evidence alone cannot uniquely ...
AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...
In a study published in npj Digital Medicine, a team of researchers led by the University of Michigan developed a machine learning model that identified 17 environmental and social factors that can ...
This study provides a useful contribution to understanding how wearable augmentation devices interact with human proprioception, using a longitudinal design over a single session. Results demonstrate ...
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