AIMC Topic: Machine Learning
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Leveraging unsupervised machine learning techniques for detecting outliers in the daily milk yield data of dairy cows.
Journal of dairy science
Jul 16, 2025
The lactation curve is essential for developing effective feeding plans, optimizing breeding, and strategizing milk production for dairy farms. However, health disorders, as well as external factors such as heat stress, dietary changes, and certain m...
Comparison of synthetic LGE with optimal inversion time vs. conventional LGE via representation learning: Quantification of Bias in Population Analysis.
Computers in biology and medicine
Jul 16, 2025
PURPOSE: Late Gadolinium Enhancement (LGE) images are crucial elements of CMR protocols for evaluating myocardial infarct (MI) severity and size. However, these images rely on signal intensity changes and manual inversion time (TI) settings, leading ...
Beyond traditional models: Jaya-optimized ensembles for accurate heart disease prediction.
Computers in biology and medicine
Jul 16, 2025
INTRODUCTION: Heart Disease (HD) stands as the foremost reason for mortality all over the world for both men and women. Millions of people are affected worldwide every year, resulting in numerous fatalities. Timely and precise detection is essential ...
Machine Learning Prediction of Financial Toxicity in Patients with Resected Lung Cancer.
Journal of the American College of Surgeons
Jul 16, 2025
BACKGROUND: Financial toxicity (FT) refers to the financial stress and detrimental impact on quality of life experienced by patients due to treatment cost. In patients with resected lung cancer (LC), we sought to identify those at risk of developing ...
Machine Learning-Based Screening of Cosmetic Ingredients Identifies Vat Blue 6 as a Thyroid Hormone Receptor β Disruptor.
Environmental science & technology
Jul 16, 2025
Thyroid disorders are among the most prevalent endocrine conditions worldwide, exhibiting a rising incidence and disproportionately affecting women. In this study, we hypothesized that cosmetics may contain previously unidentified thyroid-disrupting ...
On-Mask Magnetoelastic Sensor Network for Self-Powered Respiratory Monitoring.
ACS nano
Jul 16, 2025
Respiratory monitoring is crucial because it provides key insights into a person's health and physiological conditions. Conventional respiratory sensing is significantly challenged by the presence of water vapor in exhaled breath. An on-mask magnetoe...
Machine Learning-Based Retention Time Prediction Tool for Routine LC-MS Data Analysis.
Journal of chemical information and modeling
Jul 16, 2025
Accurate retention time () prediction models can significantly improve liquid chromatography-mass spectrometry (LC-MS) data analysis widely used in chemical synthesis. As hundreds of thousands of syntheses are performed annually at Enamine, a large a...
Noninvasive real-time monitoring of cellular spatiotemporal dynamics via machine learning-enhanced electrical impedance spectroscopy.
Science advances
Jul 16, 2025
Monitoring cellular spatiotemporal dynamics is essential for understanding complex biological processes such as organ development and cancer progression. Using live-cell fluorescence microscopy to track cellular dynamics is often limited by dye-induc...
Which explanations do clinicians prefer? A comparative evaluation of XAI understandability and actionability in predicting the need for hospitalization.
BMC medical informatics and decision making
Jul 16, 2025
BACKGROUND: This study aims to address the gap in understanding clinicians' attitudes toward explainable AI (XAI) methods applied to machine learning models using tabular data, commonly found in clinical settings. It specifically explores clinicians'...
A novel machine learning architecture to improve classification of intermediate cases in health: workflow and case study for public health.
BMC bioinformatics
Jul 16, 2025
BACKGROUND: The practice of medicine has evolved significantly during the past decade, with the emergence of Machine Learning (ML) that offers the opportunity of personalized patient-tailored care. However, ML models still face some challenges when c...
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