New Bayesian Model Extracts Shared Microbial Signals Across Heterogeneous Studies
Researchers have introduced a statistical model designed to predict disease from microbiome data pooled across many studies, addressing a persistent ...
Tag: interpretability
AI Shows Promise for Multiple Sclerosis Diagnosis, Review Finds Validation Gaps
A systematic review of 26 studies finds AI models diagnosing multiple sclerosis with over 95 percent accuracy in some cases, ...
Unsupervised Network Produces Mechanistic Saliency Maps for Medical Image Classifiers
SalientNet is an unsupervised framework that generates mechanistically grounded saliency maps for CNN medical image classifiers, outperforming Grad-CAM, Grad-CAM++, and ...
Interpretable Bayesian Model Spots Dengue from Routine Blood Counts in Bangladesh
A proof-of-concept study in Bangladesh shows a Tree-Augmented Naive Bayes model using routine complete blood count data detected dengue with ...
Gaussian Process Model Learns Interpretable Graphs for Clinical Forecasting
A new Gaussian process framework learns sparse, ordered dependency graphs from irregular electronic health records while improving forecast accuracy and ...
Machine learning disease prediction models rely heavily on one interpretability method, review finds
A systematic review of 82 studies found SHAP dominated interpretability methods in machine learning disease prediction, while calibration, stability and ...
AI Framework Halves Symptom List for Traditional Chinese Medicine Syndrome Diagnosis
A two-stage AI framework uses a large language model and evolutionary feature selection to halve the symptom set for Traditional ...
Machine learning predicts strength of nanoparticle-modified basalt fiber composites
Eight machine learning models trained on published experimental data predict the tensile and flexural strength of nanoparticle-modified basalt fiber reinforced ...
Bayesian Framework Merges Clinical Expertise With Machine Learning Diagnosis
A new Bayesian framework called PIML combines machine learning analysis of electrical impedance signals with clinical prior knowledge, improving diagnostic ...
Blueprint embeds explainability into AI systems from the ground up
Researchers propose a modular multi-agent framework, SoS-ML, that generates evidence-based explanations from internal model representations rather than post-hoc justifications.
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Mothers who receive childcare support from maternal grandparents show more parental warmth, finds NTU Singapore study
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University of Seville Breaks 120-Year-Old Mystery, Revises a Key Einstein Concept
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Bee body mass, pathogens and local climate influence heat tolerance
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Researchers record first-ever images and data of a shark experiencing a boat strike
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Groundbreaking Clinical Trial Reveals Lubiprostone Enhances Kidney Function
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