AIMC Topic: Machine Learning

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Predicting myopia risk using a machine learning model based on fundus imageomics.

Scientific reports
The purpose of this study was to develop a machine learning-based model using quantitative color fundus photography (CFP) data to predict myopia risk in school-age children, based on the axial length/corneal curvature radius (AL/CR) ratio, and to ide...

Factors Associated With Suicidal Ideation Among Persons With Disabilities in South Korea: Retrospective Observational Study.

JMIR formative research
BACKGROUND: South Korea has the highest suicide rate among the Organisation for Economic Co-operation and Development nations, with particularly elevated figures among persons with disabilities. Research has shown a strong correlation between suicida...

An Interpretable Hybrid AI Model for Breast Fine Needle Aspiration Cytology Image Classification.

Journal of medical systems
While Fine needle aspiration cytology (FNAC) and mammography are both used to diagnose breast lesions, FNAC is generally more accurate than mammograms for predicting breast cancer. It is also gaining popularity as an early detection tool due to its r...

An approach to make general practitioner referrals suitable for artificial intelligence deployment.

The New Zealand medical journal
Outpatient referrals for hospital specialist assessment are an increasing workload that carry significant risk if not attended to in a timely manner. This viewpoint discusses how decision support (including artificial intelligence and machine learnin...

Evaluating the clinical readiness of artificial intelligence in EEG-based epilepsy diagnosis.

Journal of neural engineering
Automated electroencephalography (EEG)-based epilepsy diagnosis has reported near-perfect accuracies for almost two decades on a benchmark dataset, yet virtually no system is used in routine care. We critically re-examined this translation gap by rep...

Machine learning-guided identification and simulation-based validation of potent JAK3 inhibitors for cancer therapy.

PloS one
Janus kinase 3 (JAK3) is a hematopoietic-specific kinase implicated in cytokine signaling and immune dysregulation and has recently been associated with cancer progression. However, selective and potent JAK3 inhibitors remain underdeveloped. In this ...

Descriptor-First Approach for ADMET Prediction in the PolarisHub Antiviral Challenge.

Journal of chemical information and modeling
The prediction of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties remains a central bottleneck in small-molecule discovery. We present the third-place solution from the PolarisHub Antiviral Competition, covering five ...

Deconvoluting Biophysical Factors that Influence Long-Term Aggregation Rates of High-Concentration Monoclonal Antibody Formulations.

Molecular pharmaceutics
Efficient determination of developable protein drug candidates and stable solution conditions is a key challenge in industrial drug development. Protein aggregation is difficult to predict and can lead to challenges in manufacturing, storage, and pat...

Combining Retip Retention Time Prediction with High-Resolution Mass Spectrometry: A Systematic Analysis of - Conducted for the First Time.

Analytical chemistry
- Herbal Pair (SEHP) is one of the classic Chinese herbal formulas for treating Alzheimer's disease (AD), but its complex chemical composition renders traditional analytical methods inefficient. Retention time (RT) provides complementary information ...

Machine Learning for Time-Resolved Selectivity Analysis in Methanol-To-Olefins Reaction.

Journal of chemical information and modeling
The methanol-to-olefins (MTO) process, a cornerstone reaction in modern coal chemical industries, generates complex time-dependent product selectivity profiles that challenge conventional data-driven modeling. Although machine learning (ML) has emerg...