Artificial Intelligence Medical Compendium

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

Showing 20,171 to 20,180 of 215,962 articles

CBAM-Xception: An Attention-Guided Framework for Skin Cancer Classification.

Journal of imaging informatics in medicine May 12, 2026
Skin cancer is a potentially fatal disease that requires early and accurate diagnosis to improve patient outcomes. Deep learning has shown promise in automating skin lesion classification; however, many existing models suffer from limited interpretab... read more 

Deep Learning Framework for Early Detection of Pancreatic Cancer Using Multi-modal Medical Imaging Analysis.

Journal of imaging informatics in medicine May 12, 2026
Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal forms of cancer, with a five-year survival rate below 10% primarily due to late detection [1]. This research develops and validates a deep learning framework for early PDAC detect... read more 

Transfer learning for Multi-institutional Classification of Intussusception and Splenomegaly in Pediatric Abdominal Radiographs.

Journal of imaging informatics in medicine May 12, 2026
To address diagnostic delays in pediatric abdominal emergencies, this study aimed to develop and validate multi-institutional deep learning models for detecting intussusception and splenomegaly on abdominal radiographs, thereby evaluating their poten... read more 

Estradiol loss, the "estrobolome," and midlife symptoms: what the gut microbiome adds to menopause care.

Menopause (New York, N.Y.) May 12, 2026
IMPORTANCE AND OBJECTIVE: Menopause is characterized by sustained estradiol decline affecting vasomotor, metabolic, skeletal, and neurobehavioral systems. Emerging evidence suggests that the gut microbiome may interact with endocrine pathways during ... read more 

Public Expectations for Food and Drug Administration Approval of AI-Based Clinical Decision Support Tools: Quantitative Study.

JMIR AI May 12, 2026
BACKGROUND: Regulation of artificial intelligence (AI) has been slow relative to the pace of its integration into health care. Several AI diagnostic tools for diabetic retinopathy (DR) have already received Food and Drug Administration (FDA) clearanc... read more 

Machine learning based classification of intraoperative EMG signals recorded during brain tumor surgeries: a pooled data approach for large-scale analysis and real-time applications.

Computer methods in biomechanics and biomedical engineering May 12, 2026
This study analyzes a publicly available, 7-class iEMG dataset from West China Hospital to prevent nerve damage during brain tumor surgery. Trees, SVM, KNN, Neural Networks, Random Forest, Naive Bayes and 1D-CNN, LSTM, CNN-LSTM models were evaluated.... read more 

Frequency-Aware Domain Generalization.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society May 12, 2026
Deep Neural Networks (DNNs) exhibit surprising zero-shot generalization and emergent phenomena across various tasks. However, the underlying mechanisms behind these behaviors remain unclear. By analyzing the perception of image frequencies by DNNs, w... read more 

ASA-ED: Automated Stress Assessment Via Emotion-Awareness-Driven Deep Hybrid Learning Fusing MTF and RP.

IEEE journal of biomedical and health informatics May 12, 2026
Currently, most studies on mental stress evaluation mainly focus on classification tasks, while research on accurately estimating continuous stress levels using deep learning for early identification remains limited. This study proposes an end-to-end... read more 

MPAN: A Multi-Prototype Adaptive Network for Few-Shot EEG-Based Biometric Recognition.

IEEE journal of biomedical and health informatics May 12, 2026
Biometric recognition based on electroencephalography (EEG), which captures intrinsic neural dynamics via scalp-recorded electrical activity, has shown great promise. Most existing studies leverage deep learning to enhance recognition performance. Ho... read more 

Out-of-Distribution Generalization and Detection With Limited Source Data.

IEEE transactions on cybernetics May 12, 2026
Out-of-distribution (OOD) generalization and detection have received significant attention in recent years, focusing primarily on addressing covariate shifts and category shifts in modern machine learning problems, respectively. However, most existin... read more 
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