Artificial Intelligence Medical Compendium

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

Showing 58,681 to 58,690 of 227,634 articles

An integrated machine learning framework for developing a transcriptomic analysis and machine learning-based diagnostic model of gout based on sleep disorder-related genes.

Medicine Jan 23, 2026
Gout, often comorbid with sleep disorders (SDs), is prevalent in inflammatory arthritis. This comorbidity is notable in patients with impaired renal function requiring blood purification, with unclear underlying mechanisms. This study integrated tran... read more 

The multi-omics and Mendelian randomization analyses unveiled potential marker genes in the progression of glioblastoma.

Medicine Jan 23, 2026
In glioma research, identifying key molecules for predicting patient prognosis is challenging due to high heterogeneity. This study explores the correlation between alternative splicing (AS) and glioma prognosis, aiming to identify molecular markers ... read more 

Comparative analysis of multimodal large language models GPT-4o and o1 versus clinicians in clinical case challenge questions: Retrospective cross-sectional study.

Medicine Jan 23, 2026
Generative pretrained transformer 4 (GPT-4) has demonstrated strong performance in standardized medical examinations but has limitations in real-world clinical settings. To address these limitations, the multimodal GPT-4o model integrates text and im... read more 

Computational design of intrinsically disordered proteins.

Current opinion in structural biology Jan 23, 2026
Protein design has the potential to revolutionize biotechnology and medicine. While most efforts have focused on proteins with well-defined structures, increased recognition of the functional significance of intrinsically disordered regions, together... read more 

Evaluating the efficacy of large language models in predicting intensive care unit admission needs.

Journal of critical care Jan 23, 2026
BACKGROUND: Timely identification and transfer of critically ill patients to intensive care units (ICUs) are crucial to reducing morbidity and mortality. Delayed ICU admission is linked to higher mortality, emphasizing the need for efficient predicti... read more 

An exploratory study on the relationship between renal cell carcinoma and CAFs infiltration by integrating Pathomics and collagen features.

Translational oncology Jan 23, 2026
OBJECTIVE: Cancer-associated fibroblasts (CAFs) are a critical component of the tumor microenvironment and play a significant role in renal cell carcinoma (RCC) progression and treatment response. However, current methods for evaluating CAFs infiltra... read more 

Increased moisture stress and weakened resilience to aridity limit global greening.

The Science of the total environment Jan 23, 2026
The "Greening Earth" and rising aridity are both climate change signatures. We investigate the response of global photosynthesis to moisture stress (higher demand and lower availability of moisture) in current (2000-2021) and future climate scenarios... read more 

A framework for developing machine learning-based chemical fingerprinting models using large gas chromatograph-mass spectrometer datasets: Application to oil spill residues classification.

The Science of the total environment Jan 23, 2026
Chemical fingerprinting is a key environmental forensics technique used in oil spill investigations to identify the source and type of oil in spill residues. Conventional approaches rely on detecting individual petroleum biomarkers in gas chromatogra... read more 

National-scale open cattle feedlot detection using deep learning and high-resolution aerial images: Spatial distribution and animal welfare analysis.

The Science of the total environment Jan 23, 2026
Open cattle feedlots are major animal feeding operations in the United States, characterized by outdoor confinement, high stocking densities, and regulated feeding practices. However, a comprehensive national database of these facilities remains limi... read more 

Predicting the Efficacy of Breast Cancer Neoadjuvant Chemotherapy Using Ultrasonography and Machine Learning.

Ultrasound in medicine & biology Jan 23, 2026
OBJECTIVE: This study aimed to develop a machine learning model based on ultrasonography (US) and clinicopathological features to predict pathological complete response (pCR) following neoadjuvant chemotherapy (NAC) in patients with breast cancer. Th... read more 
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