Machine learning predicts who will decline faster in Alzheimer’s disease using routine clinic data
Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...
Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...
Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
Abstract: Brain tumors rank among the most lethal forms of cancer, and their early detection is crucial for improving patient outcomes. Beyond timely identification, accurately determining tumor type ...
Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...
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