Artificial Intelligence Medical Compendium

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

Showing 10,491 to 10,500 of 209,311 articles

Re-M3Dr: Rebalanced MultiModal Mean Deviation Regression

arXiv May 26, 2026
Mean Deviation (MD) is a critical metric for assessing visual field loss in ophthalmology. While previous work has focused solely on predicting MD from Optical Coherence Tomography (OCT), it is intuitive to assume that combining OCT with another imag... read more 
Computer Vision and Pattern Recognition

Immersive spatial computing in neurosurgery.

British journal of neurosurgery May 26, 2026
PURPOSE: Immersive spatial computing technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), are increasingly applied across the neurosurgical pathway. This paper explores their evolution and modern role in crani... read more 

Determinants of maternal postnatal care utilization in Bangladesh: A machine learning and SHAP-based analysis of BDHS 2022 data.

PloS one May 26, 2026
Postnatal care (PNC) plays a crucial role in minimizing maternal and neonatal morbidity and mortality, but the uptake of services in Bangladesh remains below the recommended level. Although logistic regression has been widely used, it may miss comple... read more 

Moving beyond the benchmarks: Five foundational principles for meaningful AI evaluation in healthcare.

PLOS digital health May 26, 2026
Rapid integration of Large Language Models (LLMs) into healthcare has exposed a critical disconnect between technical performance and clinical value. While state-of-the-art models achieve impressive scores on standardized medical examinations, their ... read more 

Development and evaluation of AI model with deep learning for segmentation of extraocular muscles in thyroid eye disease.

PloS one May 26, 2026
PURPOSE: To develop and evaluate an AI model for the segmentation of extraocular muscles (EOMs) using Magnetic Resonance Imaging (MRI). DESIGN: Single-center study with retrospective study. METHODS: The study included 52 patients with thyroid eye dis... read more 

Correction: AI-powered detection of cyberbullying in short-form video content: A hybrid deep learning framework.

PloS one May 26, 2026
[This corrects the article DOI: 10.1371/journal.pone.0338799.]. read more 

DREAMER-S: Deep leaRning-Enabled Attention-based Multiple-instance approaches with Explainable Representations for Spatial biology.

PLoS computational biology May 26, 2026
Identifying image features that associate strongly with diagnostic or prognostic classes in large-scale, multi-channel spatial imaging is challenging without pixel-level annotations. We present DREAMER-S, an attention-based multiple-instance learning... read more 

A hybrid machine learning and explainable AI framework for optimizing risk-based authentication.

PloS one May 26, 2026
As online platforms continue to grow, the need for strong authentication mechanisms becomes increasingly important to protect sensitive information and networks. Risk-Based Authentication (RBA) is an adaptive approach that dynamically adjusts authent... read more 

Deepfake perpetrator conversation for adults with sexual abuse-related posttraumatic stress disorder: intervention development and multiple baseline study protocol.

European journal of psychotraumatology May 26, 2026
Background: A conversation between a victim and a perpetrator of sexual abuse has the potential to reduce posttraumatic stress disorder (PTSD) symptoms in the victim. However, an actual conversation may not always be possible or feasible. Deepfake te... read more 

High-resolution automated mapping of potential Aedes larval container habitats using drone imagery and supervised machine learning in Dar es Salaam, Tanzania.

PLoS neglected tropical diseases May 26, 2026
Larval source management is a key strategy to control the spread of Aedes-borne viral diseases including dengue, Zika, chikungunya, and yellow fever. However, locating potential larval habitats through traditional field methods is challenging and lab... read more 
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