AIMC Topic: Machine Learning

Clear Filters Showing 9921 to 9930 of 34417 articles

Artificial intelligence in andrology - fact or fiction: essential takeaway for busy clinicians.

Asian journal of andrology
Artificial intelligence (AI) is revolutionizing the current approach to medicine. AI uses machine learning algorithms to predict the success of therapeutic procedures or assist the clinician in the decision-making process. To date, machine learning s...

Assessing global carbon sequestration and bioenergy potential from microalgae cultivation on marginal lands leveraging machine learning.

The Science of the total environment
This comprehensive study unveils the vast global potential of microalgae as a sustainable bioenergy source, focusing on the utilization of marginal lands and employing advanced machine learning techniques to predict biomass productivity. By identifyi...

Classification machine learning to detect de facto reuse and cyanobacteria at a drinking water intake.

The Science of the total environment
Harmful algal blooms (HABs) or higher levels of de facto water reuse (DFR) can increase the levels of certain contaminants at drinking water intakes. Therefore, the goal of this study was to use multi-class supervised machine learning (SML) classific...

A model for identifying potentially inappropriate medication used in older people with dementia: a machine learning study.

International journal of clinical pharmacy
BACKGROUND: Older adults with dementia often face the risk of potentially inappropriate medication (PIM) use. The quality of PIM evaluation is hindered by researchers' unfamiliarity with evaluation criteria for inappropriate drug use. While tradition...

Lung Adenocarcinoma Systems Biomarker and Drug Candidates Identified by Machine Learning, Gene Expression Data, and Integrative Bioinformatics Pipeline.

Omics : a journal of integrative biology
Lung adenocarcinoma (LUAD) is a significant planetary health challenge with its high morbidity and mortality rate, not to mention the marked interindividual variability in treatment outcomes and side effects. There is an urgent need for robust system...

AttenGpKa: A Universal Predictor of Solvation Acidity Using Graph Neural Network and Molecular Topology.

Journal of chemical information and modeling
Rapid and accurate calculation of acid dissociation constant (p) is crucial for designing chemical synthesis routes, optimizing catalysts, and predicting chemical behavior. Despite recent progress in machine learning, predicting solvation acidity, es...

Varroa Mite Counting Based on Hyperspectral Imaging.

Sensors (Basel, Switzerland)
Varroa mite infestation poses a severe threat to honeybee colonies globally. This study investigates the feasibility of utilizing the HS-Cam and machine learning techniques for Varroa mite counting. The methodology involves image acquisition, dimensi...

Predicting blood-brain barrier permeability of molecules with a large language model and machine learning.

Scientific reports
Predicting the blood-brain barrier (BBB) permeability of small-molecule compounds using a novel artificial intelligence platform is necessary for drug discovery. Machine learning and a large language model on artificial intelligence (AI) tools improv...

Factors of acute respiratory infection among under-five children across sub-Saharan African countries using machine learning approaches.

Scientific reports
Symptoms of Acute Respiratory infections (ARIs) among under-five children are a global health challenge. We aimed to train and evaluate ten machine learning (ML) classification approaches in predicting symptoms of ARIs reported by mothers among child...