Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 24,761 to 24,770 of 217,472 articles

Molecular characterisation of progressive pulmonary sarcoidosis: protocol for a longitudinal multi-centre study to develop peripheral blood circulating biomarkers for predicting pulmonary sarcoidosis progression.

BMJ open
INTRODUCTION: Sarcoidosis is a heterogeneous granulomatous disease with highly variable clinical trajectories, yet no validated biomarkers exist to distinguish progressive sarcoidosis (P-sarcoidosis) from non-progressive disease (NP-sarcoidosis). Thi... read more 

Evolution and forecasting of antiretroviral therapy utilisation in British Columbia: a population-level analysis of provincial drug treatment programme data, 2014-2024.

BMJ open
OBJECTIVE: To characterise temporal trends in antiretroviral therapy (ART) utilisation and forecast short-term changes in regimen distribution within a provincial HIV treatment programme. DESIGN: Population-level longitudinal analysis of administrati... read more 

MOFSynth-ADV: An Open-Source Engine for Synthesizability Evaluation of Metal-Organic Frameworks.

Journal of chemical information and modeling
We present MOFSynth-ADV, an advanced iteration of the MOFSynth tool designed to evaluate the synthetic feasibility of Metal-Organic Frameworks (MOFs). By integrating the Atomic Simulation Environment (ASE) to leverage extended tight-binding (xTB) and... read more 

Advances in Cell Therapy for Neural Repair.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Neural repair remains one of the foremost challenges in modern neuroscience, as damage to the central nervous system caused by injury or neurodegenerative disease often leads to irreversible loss of function. The advent and rapid evolution of utilizi... read more 

Structural and Electronic Features-Integrated Machine Learning Framework for High-Throughput Prediction of Organic Pollutant Reactivity.

Environmental science & technology
Understanding and predicting the reactivity of organic pollutants toward reactive species is crucial for designing efficient and targeted degradation strategies for advanced oxidation processes. However, the structural complexity and chemical diversi... read more 

Rethinking Link Prediction for Directed Graphs.

IEEE transactions on pattern analysis and machine intelligence
Link prediction for directed graphs is a crucial task with diverse real-world applications. Recent advances in embedding methods and Graph Neural Networks (GNNs) have shown promising improvements. However, these methods often lack a thorough analysis... read more 

From Convergence to Generalization: Stability of Stationary-Point Learning Algorithms.

IEEE transactions on pattern analysis and machine intelligence
Algorithmic stability is a fundamental concept in learning theory for studying the generalization guarantees of learning algorithms. A notable limitation of classical stability analyses is that they often require convexity assumptions to obtain nontr... read more 

EEG-VLM: A Hierarchical Vision-Language Model With Multi-Level Feature Alignment and Visually Enhanced Language-Guided Reasoning for EEG Image-Based Sleep Stage Prediction.

IEEE journal of biomedical and health informatics
Sleep stage classification based on electroencephalography (EEG) is fundamental for assessing sleep quality and diagnosing sleep-related disorders. However, most traditional machine learning methods rely heavily on prior knowledge and handcrafted fea... read more 

Bias Alleviation through Network Pruning for Sparse and Debiased Models.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Pruning is a highly effective method for reducing the size of neural networks with negligible impact on their average performance. However, recent studies have revealed that pruning actually amplifies the bias in the models, leading to decreased perf... read more