Artificial Intelligence Medical Compendium

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

Showing 54,591 to 54,600 of 226,183 articles

The paradox of trust in health care in the age of social media.

Lancet (London, England)
Health systems worldwide face two fundamental and connected challenges: pervasive misinformation and disinformation and eroding public trust. This erosion reveals a paradox at the heart of contemporary science-society relations: the more science succ... read more 

Integrated HS-GC-IMS and E-nose analysis reveals aroma differentiation in representative Chinese high-quality rice varieties.

Food chemistry
Aroma is a key determinant of rice quality. This study systematically examined the divergence in aroma profiles between high-quality indica and japonica rice varieties grown across distinct ecological regions of China. We employed an integrated analy... read more 

Novel umami peptides from Cherry Valley duck meat extract: Identification, sensory characterization, and taste perception mechanism.

Food chemistry
This study aims to identify the umami peptide in duck meat and study its interaction with the T1R1/T1R3 receptor. Through computational machine learning prediction and molecular docking screening, six novel umami peptides were found, with a sensory t... read more 

DisSubFormer: A subgraph transformer model for disease subgraph representation and comorbidity prediction.

Computational biology and chemistry
Disease comorbidity-the co-occurrence of multiple diseases in the same individual-is increasingly prevalent and poses major clinical and biological challenges. Computational approaches for studying disease relationships and predicting comorbidity hav... read more 

Multi-Scale pattern-Aware task-Gating network for aerial small object detection.

Neural networks : the official journal of the International Neural Network Society
With the advancement of high-precision remote sensing equipment and precision measurement technology, object detection based on remote sensing images (RSIs) has been widely used in military and civilian fields. Different from traditional general-purp... read more 

An explainable and transferable deep learning framework for spatiotemporal urban flood prediction by integrating Vision Transformer and U-Net.

Water research
Urban flood has become an increasingly frequent and severe hazard under intensified climate change and rapid urbanization, yet real-time prediction remains challenging. Existing data-driven models often suffer from limited physical plausibility and t... read more 

Improving Diagnostic Precision in Thyroid Pathology by Synergistic Use of AI and Molecular Markers.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
OBJECTIVES: For indeterminate thyroid nodules, molecular tests offer high negative predictive value (NPV), reducing missed malignancies, but have limited positive predictive value (PPV), potentially leading to unnecessary surgeries. We evaluated how ... read more 

Predictive value of tear lipidomics biomarkers for TAO activity and relationship with clinical characteristics.

Experimental eye research
The objective of this study was to explore the lipid metabolic changes in the active thyroid-associated ophthalmopathy (TAO) through tear lipidomics analysis, screen for biomarkers related to disease activity, and analyze their correlation with clini... read more 

Machine learning-enabled meta-analysis reveals the effect of microplastics on nitrogen removal performance in constructed wetlands and its potential mechanisms.

Environmental research
Constructed wetlands (CWs) are an effective wastewater treatment system and an important sink for microplastics (MPs). However, MPs impacts on nitrogen removal performance of CWs remain unclear. Here, we collected 1903 datasets from 34 studies for a ... read more 

AI-based analysis of label-free live cell imaging of T-cell mediated tumor killing assay enables competitive and robust hit calling.

SLAS discovery : advancing life sciences R & D
For the discovery and optimization of personalized cancer treatments using immune cell therapeutics, such as T-cell receptor (TCR-T) therapy and bispecific antibodies (BsAbs), robust functional activity of candidates must be confirmed in immune-media... read more