Artificial Intelligence Medical Compendium

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

Showing 50,481 to 50,490 of 224,814 articles

Evolution from Analyte to Sensitive Signal Probe: Norfloxacin-Based Assembly for Machine-Learning-Assisted Discrimination of Phosphates and Monitoring of ATP Hydrolysis.

Analytical chemistry
The development of sensor arrays for effective discrimination of structurally similar physiological phosphates (PPs) in mixtures presents a considerable challenge. We propose a new strategy based on concentration-regulated supramolecular assembly to ... read more 

Molecular fluorophore dimerization: a new paradigm for precision phototheranostics.

Chemical Society reviews
Molecular fluorophore dimerization has recently emerged as a powerful and versatile design strategy in phototheranostics, offering a distinct regulatory regime that is fundamentally different from conventional single-molecule, polymeric, or aggregate... read more 

TropMol: a cloud-based web tool for virtual screening and early-stage prediction of acetylcholinesterase inhibitors using machine learning.

Organic & biomolecular chemistry
Alzheimer's disease (AD) is the most common type of dementia, accounting for at least two-thirds of dementia cases in people aged 65 and older. Numerous approaches have been studied for the treatment of this disease, including the cholinergic hypothe... read more 

Machine Learning-Assisted Detection of Phosgene and Acetyl Chloride via a Dual-Probe Fluorescent Platform with Differential Reactivity.

Analytical chemistry
Phosgene and acyl chlorides are highly toxic chemicals that pose serious threats to human health and environmental safety, yet their rapid and reliable detection remains a major challenge due to their high reactivity and environmental interferences. ... read more 

Unlocking Multiscale Allosteric Mechanisms: Advanced Computational Strategies for Drug Discovery.

Medicinal research reviews
Multiscale allosteric mechanisms refer to regulatory processes in proteins that involve coordinated conformational changes and signal transmission occurring across multiple spatial and temporal scales. Exploiting these mechanisms provides promising o... read more 

Vector-Based Comparison and Average Slope Can Refine Bioequivalence Claims: A Machine and Deep Learning Approach.

Biopharmaceutics & drug disposition
This study explored the advantages of two innovative concepts: AS and VBC. AS is a pharmacokinetic parameter that measures absorption rates, whereas VBC analyzes clinical endpoints as vectors, breaking them into independent components. Together, thes... read more 

NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Chromatin loops play a crucial role in gene regulation and cellular function, providing key insights into understanding the 3D structure of the genome and its impact on cellular homeostasis. Nanopore sequencing technology, with its advantages in simu... read more 

Indirect, Machine Learning-Based Suicide Risk Screening: Evidence from Cross-National Validation.

European psychiatry : the journal of the Association of European Psychiatrists
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Smart Optogenetics for Real-Time Automated Control of Cardiac Electrical Activity.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Control theory underpins the stabilization of dynamic systems, including cardiac tissue, where disruptions in electrical conduction cause arrhythmias. Current treatments either act rapidly but without precision or deliver targeted interventions that ... read more 

Klebsiella oxytoca: an opportunistic bacterial pathogen that poses challenges for treatment and vaccine development.

Future microbiology
Klebsiella oxytoca is a clinically significant opportunistic bacterium that contributes to global morbidity and mortality. Despite its clinical relevance, the genomic diversity, virulence factors, and immune evasion mechanisms of this pathogen are no... read more