AIMC Topic: Machine Learning

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Predicting mothers' exclusive breastfeeding for the first 6 months: Interface creation study using machine learning technique.

Journal of evaluation in clinical practice
BACKGROUND: Machine learning techniques (MLT) build models to detect complex patterns and solve new problems using big data.

An integrated machine learning framework for developing and validating a diagnostic model of major depressive disorder based on interstitial cystitis-related genes.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) and interstitial cystitis (IC) are two highly debilitating conditions that often coexist with reciprocal effect, significantly exacerbating patients' suffering. However, the molecular underpinnings linking ...

Clinical evaluation of a machine learning-based dysphagia risk prediction tool.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: The rise of digitization promotes the development of screening and decision support tools. We sought to validate the results from a machine learning based dysphagia risk prediction tool with clinical evaluation.

Loss of micropollutants on syringe filters during sample filtration: Machine learning approach for selecting appropriate filters.

Chemosphere
Prefiltration before chromatographic analysis is critical in the monitoring of environmental micropollutants (MPs). However, in an aqueous matrix, such monitoring often leads to out-of-specification results owing to the loss of MPs on syringe filters...

Usability, Acceptability, and Implementation of Artificial Intelligence (AI) and Machine Learning (ML) Techniques in Surgical Coaching and Training: A Scoping Review.

Journal of surgical education
OBJECTIVE: To define the current state of peer-reviewed literature demonstrating the usability, acceptability, and implementation of artificial intelligence (AI) and machine learning (ML) techniques in surgical coaching and training.

Machine Learning for Polymer Design to Enhance Pervaporation-Based Organic Recovery.

Environmental science & technology
Pervaporation (PV) is an effective membrane separation process for organic dehydration, recovery, and upgrading. However, it is crucial to improve membrane materials beyond the current permeability-selectivity trade-off. In this research, we introduc...

Adaptive Workflows of Machine Learning Illuminate the Sequential Operation Mechanism of the TAK1's Allosteric Network.

Biochemistry
Allostery is a fundamental mechanism driving biomolecular processes that holds significant therapeutic concern. Our study rigorously investigates how two distinct machine-learning algorithms uniquely classify two already close-to-active DFG-in states...

Machine learning-based exploration of biochar for environmental management and remediation.

Journal of environmental management
Biochar has a wide range of applications, including environmental management, such as preventing soil and water pollution, removing heavy metals from water sources, and reducing air pollution. However, there are several challenges associated with the...

Machine-learning classifier models for predicting sarcopenia in the elderly based on physical factors.

Geriatrics & gerontology international
AIM: As the size of the elderly population gradually increases, musculoskeletal disorders, such as sarcopenia, are increasing. Diagnostic techniques such as X-rays, computed tomography, and magnetic resonance imaging are used to predict and diagnose ...