Artificial Intelligence Medical Compendium

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

Showing 67,251 to 67,260 of 232,511 articles

From 16S rRNA to deep learning: Evolution of computational approaches in human microbiome studies.

Computational biology and chemistry
The human microbiome plays a vital role in maintaining physiological balance and influencing immunity, metabolism, and disease development. Over the past decade, the field has witnessed a remarkable transition from traditional 16S rRNA sequencing and... read more 

Development and Validation of an Automated Pipeline for the Detection of Monteggia Fracture Dislocations in Pediatric Radiographs.

Journal of pediatric orthopedics
BACKGROUND: Monteggia fractures are a complex elbow injury that can be missed in up to 50% of pediatric elbow injuries during initial radiographic assessment due to their subtlety. The development of more advanced diagnostic tools is crucial to ensur... read more 

Literature-informed ensemble machine learning for three-year diabetic kidney disease risk prediction in type 2 diabetes: Development, validation, and deployment of the PSMMC NephraRisk model.

Diabetes, obesity & metabolism
INTRODUCTION: Diabetic kidney disease (DKD) and diabetic nephropathy (DN) affect around 40% of diabetic patients but lack accurate risk prediction tools that include social determinants and demographic complexity. We developed and validated an ensemb... read more 

Machine learning-driven GC-MS analysis for assessing the contribution of amino acids in the flavor of cheese maturing at high temperature.

International journal of food microbiology
Branched-chain (BCAA) and aromatic amino acids (AAA) are precursors of volatile compounds with pleasant flavors in cheese. In this study, BCAA and AAA were added to cheese which matured at 30 °C for 7 days to assess their effects on accelerating chee... read more 

Object-centric proto-symbolic behavioural reasoning from pixels.

Neural networks : the official journal of the International Neural Network Society
Autonomous intelligent agents must bridge computational challenges at disparate levels of abstraction, from the low-level spaces of sensory input and motor commands to the high-level domain of abstract reasoning and planning. A key question in design... read more 

Cellular and molecular determinants of lymph node metastasis in papillary thyroid carcinoma: Integrated multi-omics profiling and machine learning models.

Computational biology and chemistry
The mechanisms underlying lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) remain elusive. This study integrated single-cell RNA sequencing (scRNA-seq) data, spatial transcriptomics (ST) data, and bulk transcriptomic data. Analyses re... read more 

Plant-derived angiotensin-converting enzyme regulatory peptides: Potential sources, mechanisms and applications.

Food chemistry
Angiotensin-converting enzyme (ACE) is mainly categorized into ACE-1 and ACE-2, both of which play significant roles in human physiological balance and metabolism. Compared to synthetic drugs, food-derived natural peptides offer unique advantages reg... read more 

Global mapping of pharmaceutical ecological risk in rivers using machine learning: drivers, hotspots, and compounded water stress.

Water research
Pharmaceuticals serve as a double-edged sword: while essential for health care, they are also ubiquitous pollutants that threaten ecosystem. The vast scale of global surface waters makes comprehensive pharmaceutical monitoring impractical, resulting ... read more 

Enabling efficient low-bit quantization based on matrix product operators for KV cache compression.

Neural networks : the official journal of the International Neural Network Society
Large language models (LLMs), despite their remarkable successes, remain significantly expensive to implement. Among various strategies, key-value cache (KV cache) stands out as a crucial technique for expediting the inference of LLMs, yet it comes w... read more 

Diagnostic Performance of AI-Assisted Coronary CT Angiography: A Systematic Review and Meta-Analysis.

European journal of radiology
BACKGROUND: Coronary computed tomography angiography (CCTA) is vital for diagnosing ischemic heart disease, yet its accuracy is unreliable due to varying reader expertise. Artificial Intelligence (AI)-driven automated stenosis assessment offers promi... read more