AIMC Topic: Machine Learning
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A radiomics-based interpretable model integrating delayed-phase CT and clinical features for predicting the pathological grade of appendiceal pseudomyxoma peritonei.
BMC medical imaging
Jul 28, 2025
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
Jul 28, 2025
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
Jul 28, 2025
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
Jul 28, 2025
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...
Semantic classification of Indonesian consumer health questions.
Journal of biomedical semantics
Jul 28, 2025
PURPOSE: Online consumer health forums serve as a way for the public to connect with medical professionals. While these medical forums offer a valuable service, online Question Answering (QA) forums can struggle to deliver timely answers due to the l...
Ecological epidemiology insights into clonorchiosis endemicity in Guangxi, China and Vietnam: a comprehensive machine learning analysis.
International journal of health geographics
Jul 28, 2025
BACKGROUND: Clonorchis sinensis, the liver fluke responsible for clonorchiosis, presents a persistent public health burden in Guangxi (Southern China) and Vietnam. Its transmission is influenced by a complex interplay of ecological, climatic, and soc...
Identification of age-specific risk factors for hyperuricemia: a machine learning-driven stratified analysis in health examination cohorts.
BMC medical informatics and decision making
Jul 28, 2025
BACKGROUND: Hyperuricemia (HUA) as a global public health challenge, although its overall epidemiological characteristics have been widely reported, its age-specific risk pattern remains controversial. This study aims to reveal the risk factors of HU...
Machine Learning Predicts Drug Release Profiles and Kinetic Parameters Based on Tablets' Formulations.
The AAPS journal
Jul 28, 2025
Direct compression (DC) remains a popular manufacturing technology for producing solid dosage forms. However, the formulation optimisation is a laborious process, costly and time-consuming. The aim of this study was to determine whether machine learn...
Data Transformation to Advance AI/ML Research and Implementation in Primary Care.
Annals of family medicine
Jul 28, 2025
Artificial intelligence and machine learning (AI/ML) in health care is accelerating at a breathtaking pace. As the largest health care delivery platform, primary care is where the power, opportunity, and future of AI/ML are most likely to be realized...
Predicting Missed Appointments in Primary Care: A Personalized Machine Learning Approach.
Annals of family medicine
Jul 28, 2025
PURPOSE: Factors influencing missed appointments are complex and difficult to anticipate and intervene against. To optimize appointment adherence, we aimed to use personalized machine learning and big data analytics to predict the risk of and contrib...
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