When Biology Meets Medicine: A Perspective on Foundation Models
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
Predicting student specializations: a Machine Learning Approach based on Academic Performance
Education is a cornerstone of societal progress, equipping people with essential skills and knowledge. In today’s dynamic global society, personalized learning experiences are crucial. Data-driven methodologies, especially Educational Data Mining (EDM),
Athanasios Angeioplastis +4 more
doaj +1 more source
Corrigendum to ``Academic data derived from a university e-government analytic platform: An educational data mining approach'' [Data in Brief, Volume 49 (2023) /109357]. [PDF]
Chytas K +4 more
europepmc +1 more source
Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry
Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa +3 more
wiley +1 more source
Explainable AI and machine learning: performance evaluation and explainability of classifiers on educational data mining inspired career counseling. [PDF]
Guleria P, Sood M.
europepmc +1 more source
Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang +9 more
wiley +1 more source
Corrigendum: Educational Data Mining Techniques for Student Performance Prediction: Method Review and Comparison Analysis. [PDF]
Zhang Y +5 more
europepmc +1 more source
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
Educational Data Mining Techniques for Student Performance Prediction: Method Review and Comparison Analysis. [PDF]
Zhang Y +5 more
europepmc +1 more source
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai +10 more
wiley +1 more source

