AI Medical Compendium

Cross-Task Benchmarking of CNN Architectures

arXiv Feb 25, 2026

This project provides a comparative study of dynamic convolutional neural networks (CNNs) for various tasks, including image classification, segmentation, and time series analysis. Based on the ResNet-18 architecture, we compare five variants of CNNs... read more

Computer Vision and Pattern Recognition

Predicting postoperative atrial fibrillation: An explainable deep learning approach.

Journal of biomedical research Feb 25, 2026

A systematic review of efforts to predict day of surgery cancellation.

European journal of anaesthesiology Feb 25, 2026

BACKGROUND: Day of surgery cancellation (DOSC) for elective surgery occurs in 18% of elective surgeries worldwide with resultant impacts on patients and healthcare systems. Accurate prediction of such cancellations could yield significant benefit. OB... read more

Balancing Innovation in Artificial Intelligence With Practical Sepsis Definitions.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America Feb 25, 2026

Operationalizing Sepsis Definitions With Artificial Intelligence: Toward Smarter Antibiotic Use.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America Feb 25, 2026

Optimising descriptors to correlate stability of C- or N-doped high-entropy alloys: a combined DFT and machine-learning regression study.

Faraday discussions Feb 24, 2026

Interstitial doping is a common approach to improve the mechanical or functional properties of high-entropy alloys (HEAs); their stability is usually predicted by a specific single descriptor. Herein, we consider six types of microstructure-based des... read more

Understanding and improving compound pressures in general practice: a realist review protocol.

BJGP open Feb 24, 2026

BACKGROUND: Compound pressures (CP) impact the role of general practice in supporting human health. These pressures include climate change, pandemics, and financial crises. CP can be predictable, pre-determined, or unpredictable in nature and scope. ... read more

Regional brain age is decreased in children with sickle cell anemia.

Blood advances Feb 24, 2026

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individual's brain age, allowing calculation of the brain age gap (predicted chronological age) for use as a biomarker of brain health. We tested the DeepBrain... read more

On the use of advanced scanning transmission electron microscopy and machine learning for studying multi-component materials.

Faraday discussions Feb 24, 2026

The nanoscale distribution of elements in two multi-component materials is assessed by unsupervised machine learning methods. These are compared to elemental maps to highlight the potential shortcomings of simplistic compositional analyses. Quantific... read more

BOTANIC-0: a series of foundation models for plant genomic data

bioRxiv Feb 24, 2026

Genomic language models (gLMs) have emerged as a powerful paradigm for learning regulatory biology directly from DNA sequence. Here, we introduce Botanic0, a family of plant genomic foundation models spanning 100M to 1B parameters and pretrained on 4... read more

plant biology

Artificial Intelligence Medical Compendium