AI Medical Compendium

Machine Learning Potential-Enabled Platform for the In Silico Design of Functional Organic Molecular Crystals.

Journal of chemical information and modeling Apr 9, 2026

The design and discovery of functional molecular materials can be greatly accelerated through in silico approaches. Machine learning (ML) models, in particular, demonstrate significant promise for the rapid analysis and manipulation (and reanalysis) ... read more

Extended Rice-Thomson analysis and atomistic simulations revealing grain boundary effects on fracture in refractory high-entropy alloys.

Proceedings of the National Academy of Sciences of the United States of America Apr 9, 2026

Understanding how grain boundaries mediate fracture remains a critical challenge in designing ductile, high-performance refractory alloys. Here, we extend the Rice-Thomson criterion to account for the angle between cracks and the impinging grain boun... read more

Machine learning applications for postharvest poultry processing: a review.

Critical reviews in food science and nutrition Apr 9, 2026

Poultry meat plays a vital role in global food security due to its affordability and high-quality protein content. Its production keeps growing worldwide. This highlights the need for poultry processing facilities to operate efficiently while maintai... read more

Classification of functional brain patterns elicited by deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 9, 2026

Despite the remarkable success of deep brain stimulation (DBS) in alleviating Parkinson's disease (PD) symptoms, complexities arising from inherent inter-individual variability and the vast array of available methodologies for functional brain imagin... read more

Neural Operator: Is data all you need to model the world? An insight into the paradigm of data-driven scientific ML.

IEEE transactions on pattern analysis and machine intelligence Apr 9, 2026

Numerical approximations of partial differential equations (PDEs) are routinely employed to formulate the solution of physics, engineering, and mathematical problems involving functions of several variables, such as the propagation of heat or sound, ... read more

Sharpness-aware Fine-Tuning for OOD Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Apr 9, 2026

The out-of-distribution (OOD) detection task is crucial for the real-world deployment of machine learning models. In this paper, we propose to study the problem from the perspective of Sharpness-aware Minimization (SAM). Compared with traditional opt... read more

S3F-Net: A Multi-Modal Approach to Medical Image Classification via Spatial-Spectral Summarizer Fusion Network.

IEEE journal of biomedical and health informatics Apr 9, 2026

Convolutional Neural Networks (CNNs) have become a cornerstone of medical image analysis due to their proficiency in learning hierarchical spatial features. However, this focus on a single domain is inefficient at capturing global, holistic patterns ... read more

Spatial omics and AI for clinically actionable cancer biomarkers.

PLoS medicine Apr 9, 2026

Integrating spatial omics with artificial intelligence is likely to advance biomarker research and diagnostics, with the potential to pair mechanistic insight into spatial target biology. By developing scalable, reproducible quantification in routine... read more

Subgroup identification of disparities in buprenorphine discontinuation in opioid-use disorder: A Virtual Twins machine learning approach using nationwide United States claims data, 2006-2022.

PLOS mental health Apr 9, 2026

Buprenorphine retention is crucial for effective treatment of opioid use disorder (OUD), yet disparities in treatment discontinuation persist. This study aims to identify and quantify disparities in buprenorphine treatment retention using a machine l... read more

Development and evaluation of a multimodal feature-based predictive model for radiotherapy-induced oral mucositis in nasopharyngeal carcinoma.

PloS one Apr 9, 2026

BACKGROUND: Accurate prediction of radiation-induced oral mucositis is crucial for personalized treatment in head and neck cancer. However, developing robust predictive models utilizing high-dimensional multimodal data (CT imaging, dose distribution,... read more

Artificial Intelligence Medical Compendium