AIMC Topic: Machine Learning

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Predicting depressive symptoms through social support: a machine learning approach in military populations.

European journal of psychotraumatology
Perceived Social support has been consistently shown to reduce depressive symptoms among military personnel. However, limited research has explored how different types of support, emotional, informational, and instrumental, from multiple sources uni...

A Sn-Ta-O-doped vertical graphene electrochemical sensor based on a machine learning prediction model for monitoring cadmium in beverages.

Food chemistry
The growing diversity of beverages intensifies demand for on-site heavy metal detection to ensure safety. Multi-heteroatom co-doped graphene electrodes exhibit superior electrocatalytic activity and stability over traditional carbon-based electrodes,...

Mapping hotspots and identifying drivers of lead bioaccumulation in Oryza sativa L. in tropical agroecosystems.

Journal of hazardous materials
Tropical rice systems exhibit high annual rates of heavy metal accumulation, requiring accurate identification of accumulation drivers in rice-growing ecosystems to ensure regional food security. Therefore, we collected 229 paired soil and rice sampl...

Unveiling key pathomic features for automated diagnosis and Gleason grade estimation in prostate cancer.

BMC medical imaging
BACKGROUND: Recent advances in histology scanning technology and Artificial Intelligence (AI) offer great opportunities to support cancer diagnosis. The inability to interpret the extracted features and model predictions is one of the major issues li...

Predicting Emergency Severity Index (ESI) level, hospital admission, and admitting ward in an emergency department using data-driven machine learning.

BMC medical informatics and decision making
INTRODUCTION: Emergency departments (EDs) are critical for ensuring timely patient care, especially in triage, where accurate prioritisation is essential for patient safety and resource utilisation. Building on previous research, this study leverages...

Prediction of early postoperative complications and transfusion risk after lumbar spinal stenosis surgery in geriatric patients: machine learning approach based on comprehensive geriatric assessment.

BMC medical informatics and decision making
BACKGROUND: Lumbar spinal stenosis is one of the most common surgery-requiring conditions of the spine in the aged population. As elderly patients often present with multiple comorbidities and limited physiological reserve, individualized risk assess...

A radiomics-based interpretable model integrating delayed-phase CT and clinical features for predicting the pathological grade of appendiceal pseudomyxoma peritonei.

BMC medical imaging
OBJECTIVE: This study aimed to develop an interpretable machine learning model integrating delayed-phase contrast-enhanced CT radiomics with clinical features for noninvasive prediction of pathological grading in appendiceal pseudomyxoma peritonei (P...

Determination of milk yield in water buffaloes using multi-class logistic regression and machine learning methods.

Tropical animal health and production
In this study, Random Forest, Gradient Boosting Machines (GBM), and Support Vector Machines (SVM), Multi-Class Logistic Regression (MCLR) models were comparatively evaluated for the prediction of milk yield in water buffaloes. The study's main purpos...

Quantitative evaluation of hydrocarbon contamination in soil using hyperspectral data-a comparative study of machine learning models.

Environmental monitoring and assessment
This study aims to evaluate the applicability of existing machine learning and deep learning techniques for the rapid prediction of hydrocarbon contamination in soils using hyperspectral data. Soil samples of three types, i.e., clayey, silty, and san...

The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns.

Scientific reports
The diverse nature and timing of a clubfoot relapse pose challenges for early detection. A relapsed clubfoot typically involves a combination of deformities affecting a child's movement pattern across multiple joint levels, formed by a complex kinema...