AIMC Topic: Machine Learning

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Optimization of hemocompatibility metrics in ventricular assist device design using machine learning and CFD-based response surface analysis.

The International journal of artificial organs
Ventricular assist devices (VADs) are essential for end-stage heart failure patients, but their design must balance hydraulic efficiency and hemocompatibility to minimize blood damage. This study presents a multi-objective optimization framework inte...

Machine learning techniques for continuous genetic assignment of geographic origin of forest trees.

PloS one
Origin tracking is important to ensure use of the right seed source and trade with legally harvested timber. Additionally, it can help to reconstruct human-caused historical long-distance seed transfer and to spot mislabelling in forest field trials....

An efficient low-shot class-agnostic counting framework with hybrid encoder and iterative exemplar feature learning.

PloS one
Few-shot learning techniques have enabled the rapid adaptation of a general AI model to various tasks using limited data. In this study, we focus on class-agnostic low-shot object counting, a challenging problem that aims to achieve accurate object c...

MTSA-SC: A multi-task learning approach for individual trip destination prediction with multi-trajectory subsequence alignment and space-aware loss functions.

PloS one
Individual Trip Destination Prediction aims to accurately forecast an individual's future travel destinations by analyzing their historical trajectory data, holding significant application value in intelligent navigation, personalized recommendations...

Machine learning-driven 3D-QSAR models facilitated rapid on-site broad-spectrum immunoassay of (fluoro)quinolones using evanescent wave fiber-embedded optofluidic biochip.

Biosensors & bioelectronics
(Fluoro)quinolones (FQs) pose significant threats to public health due to their widespread use and persistence in food and water sources. Given the extensive variety of FQs, testing each compound individually is prohibitively expensive and time-consu...

Reappraising machine learning models for vascular calcification in CKD: methodological concerns and clinical gaps.

International urology and nephrology
Lin et al. (Int Urol Nephrol, 2025) contribute to the literature on abdominal aortic calcification (AAC) in chronic kidney disease (CKD) using interpretable machine learning. However, several limitations hinder its clinical applicability. The cross-s...

Measuring natural selection on the transcriptome.

The New phytologist
The level and pattern of gene expression is increasingly recognized as a principal determinant of plant phenotypes and thus of fitness. The estimation of natural selection on the transcriptome is an emerging research discipline. We here review recent...

Pelvic inflammatory disease prevalence and dietary phosphorus: A cross-sectional analysis of the National Health and Nutrition Examination Survey, 2015-2018.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: Emerging evidence suggests dietary components may modulate inflammatory conditions, yet the role of phosphorus in pelvic inflammatory disease (PID) remains unclear. This study investigated the association between dietary phosphorus intake ...

Monitoring strategies for continuous evaluation of deployed clinical prediction models.

Journal of biomedical informatics
OBJECTIVE: As machine learning adoption in clinical practice continues to grow, deployed classifiers must be continuously monitored and updated (retrained) to protect against data drift that stems from inevitable changes, including evolving medical p...

Race-Performance Parameters Differentiating World-Best From National-Level Swimmers: A Race Video Analysis and Machine-Learning Approach.

International journal of sports physiology and performance
BACKGROUND: Elite swimming performance is determined by a complex interplay of anthropometric, physiological, biomechanical, and technical factors. Previous research highlights how the 100-m freestyle demands explosive power, technical proficiency, a...