A German cheese-maker is using a vision system and machine-learning algorithms to detect any defects in its cheeses, thus ...
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...
Metabolic-associated steatotic liver disease (MASLD) is a clinically heterogeneous condition with highly variable outcomes affecting more than 30% ...
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A machine learning model may enable liver cancer risk prediction with routine clinical information
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...
Passive Brain-Computer Interfaces (pBCIs) have shown significant advancements in recent years, indicating their readiness for ...
Researchers have optimized a headspace sorptive extraction (HSSE) method coupled with gas chromatography-mass spectrometry ...
This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...
New framework combines Copilot, Claude, ChatGPT, Gemini, Perplexity, and multi-model LLMs to transform Power BI and ...
At Pittcon 2026 in San Antonio, Dr. Lenka Halámková of Texas Tech walked through a multimodal workflow that combines Raman ...
Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...
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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