Artificial Intelligence Medical Compendium

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

Showing 1,101 to 1,110 of 213,401 articles

Exploration peptide-GPCR specificity beyond homology and tertiary structure: computational insights into deorphanization and molecular mechanisms.

General and comparative endocrinology Jul 19, 2026
Peptide-responsive G protein-coupled receptors (GPCRs) play pivotal roles in a wide variety of physiological regulatory systems in animals. Despite the substantial expansion of the GPCR and endogenous peptide repertoire identified through large-scale... read more 

Predictive modeling of fluid status in hemodialysis: model development and internal validation using the MONitoring dialysis outcomes (MONDO) global database.

Renal failure Jul 19, 2026
BACKGROUND: Optimized fluid management is crucial in dialysis care because extracellular volume overload drives adverse cardiovascular outcomes. At the same time, comorbidities such as inflammation and protein energy wasting lead to decreased muscle ... read more 

Deep learning-based multi-class classification of cutaneous lesions for dermatological assessment.

Cutaneous and ocular toxicology Jul 19, 2026
BACKGROUND: Skin cancer is one of the most common malignancies worldwide, and early detection is essential for improving treatment outcomes and reducing mortality. Conventional diagnostic approaches rely on visual examination and dermoscopic analysis... read more 

Influence of artificial intelligence on xenotransplantation and regenerative medicine on the path toward ending the organ shortage.

Renal failure Jul 19, 2026
The purpose of this review is to summarize the most influential and conceptually significant publications from the past 2 years, including substantial 2026 publications, and to identify emerging directions likely to shape xenotransplantation and rege... read more 

A diffusion-conditioned representation learning framework for disease classification in medical imaging.

BMC research notes Jul 19, 2026
OBJECTIVE: Recently, deep learning models in medical imaging have undergone tremendous advancements. However, these deterministic discriminative models often tend to overfit and produce overconfident predictions. To explore a more efficient strategy,... read more 

Spatio-temporal drought dynamics in Niamey District, Niger (2005-2022): multi-index deep learning approach leveraging multi-sensor satellite and climate datasets.

Scientific reports Jul 19, 2026
In this research, we developed and applied a multi-sensor Long short-Term Memory (LSTM) pipeline for drought monitoring and analysis in the Niamey District of Niger from 2005 to 2022. Data inputs included Landsat 5 TM and Landsat 7 ETM + satellite sc... read more 

Model evaluation for automated scoring of electropenetrography waveform data from mosquitoes.

Scientific reports Jul 19, 2026
Electropenetrography (EPG) is a powerful tool for quantifying how arthropods interact with their hosts, but manually labeling EPG feeding behavior waveforms is subjective, labor-intensive, and time-consuming. Machine-learning models for supervised cl... read more 

Physics-informed multi-task learning for permeability prediction and probabilistic HFU modeling: a case study from the Lower Bahariya Reservoir, Shahd SE field Egypt.

Scientific reports Jul 19, 2026
Accurate permeability prediction is essential for reliable reservoir characterization and simulation, yet remains challenging due to complex nonlinear relationships and subsurface heterogeneity. Conventional hydraulic flow unit (HFU) methods rely on ... read more 

Adaptive test-time augmentation via KL-regularized reinforcement learning for robust visual inference.

Scientific reports Jul 19, 2026
Deep neural networks often suffer significant accuracy degradation when exposed to real-world image corruptions and distribution shifts. To overcome the limitations of fixed, input-agnostic test-time augmentation (TTA), an adaptive framework is propo... read more 

Symbolic and domain-generalized machine learning for interpretable solubility modeling in supercritical CO₂.

Scientific reports Jul 19, 2026
Accurate prediction of drug solubility in supercritical CO₂ remains challenging due to the limited generalizability of compound-specific correlations and the black-box nature of most machine learning models. This study proposes a domain-aware symboli... read more 
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