Artificial Intelligence Medical Compendium

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

Showing 59,461 to 59,470 of 227,876 articles

Machine learning-based prediction of carbohydrate productivity in continuous cultivation of Chlorella vulgaris.

Bioresource technology
Predicting carbohydrate productivity in continuous microalgae cultivation systems remains a significant technical challenge due to the non-linear nature of metabolic pathways under multiple stresses. This study applied Machine Learning (ML) models to... read more 

Comparative Analysis of Muscle Coordination Patterns During Squatting in Trained and Untrained Individuals.

Journal of applied biomechanics
Squatting, a closed-kinetic chain exercise, requires the complex coordination of multiple muscles. However, the differences in muscle coordination patterns between individuals with varying levels of exercise proficiency remain unclear. This study aim... read more 

Deep Learning-Based Classification of Slit-Lamp Photograph Quality in Microbial Keratitis.

Ophthalmology science
OBJECTIVE: Microbial keratitis (MK) is one of the leading causes of blindness in low- and middle-income countries that often requires timely diagnosis and subsequent treatment. Literature has shown that poor-quality slit-lamp photos (SLPs) can negati... read more 

Identification of antihypertensive, antidiabetic, and antioxidant peptides derived from hydrolysates of dairy white wastewaters containing milk proteins using machine learning insights.

Food research international (Ottawa, Ont.)
Dairy white wastewater (WW), a by-product of industrial cleaning processes, contains residual milk proteins that can be enzymatically converted into bioactive peptides. In this study, WW proteins were hydrolyzed using four enzymes, pepsin, trypsin, t... read more 

Generative Artificial Intelligence-Enabled Saliency Analysis of Eye Tracking in Cerebral/Cortical Visual Impairment (SET-CVI).

Ophthalmology science
PURPOSE: Children with cerebral/cortical visual impairment (CVI) have neurological conditions that impact visual pathways in the brain, leading to deficits in both lower- and higher-order visual function that can be challenging to measure, especially... read more 

BrinjalFruitX: A field-collected image dataset for machine learning and deep learning-based disease identification in brinjal fruits.

Data in brief
Brinjal (Solanum melongena) or eggplant is one of the four most essential vegetable crops that are grown in Bangladesh and contribute significantly to the agricultural industry of the country. Brinjal supports the livelihood of numerous small farmers... read more 

Data-Driven Design and Fabrication of Heat-Resistant, Ultrastrong, Lightweight Aluminum-Based Entropy Alloy by Additive Manufacturing.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Additive manufacturing (AM) of heat-resistant high-strength aluminum (Al) alloys for load-bearing components faces a fundamental dichotomy: traditional high-strength compositions suffer from hot cracking, while printable alloys lack sufficient high-t... read more 

Smart evaluation of tea quality: machine learning-assisted SERS for white tea vintage authentication and grade classification.

Food chemistry
Traditional sensory evaluation methods for tea-relying on empirical experience, visual colorimetry, and subjective taste perception-suffer from irreproducible inter-rater variability and inability to quantify bioactive markers, thus failing to establ... read more 

An anatomical hotspot for striatal dopamine-acetylcholine interactions during reward and movement

bioRxiv
Dopamine (DA) and acetylcholine (ACh) are key neuromodulators that regulate striatal circuits underlying movement and reinforcement learning. Evidence suggests that DA and ACh systems interact, but where and how interactions are expressed across stri... read more 

Pain-regulation circuitry as a predictor of chronic pain phenotypes

bioRxiv
Background: Chronic pain is a multidimensional condition in which emotional distress, negative expectations, and functional impairment signal greater disease severity. Standard diagnostic categories often fail to capture clinically meaningful heterog... read more