AIMC Topic: Machine Learning
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Comparative investigation of bagging enhanced machine learning for early detection of HCV infections using class imbalance technique with feature selection.
PloS one
Jun 26, 2025
Around 1.5 million new cases of Hepatitis C Virus (HCV) are diagnosed globally each year (World Health Organization, 2023). Consequently, there is a pressing need for early diagnostic methods for HCV. This study investigates the prognostic accuracy o...
Effect of the exposure to brominated flame retardants on hyperuricemia using interpretable machine learning algorithms based on the SHAP methodology.
PloS one
Jun 26, 2025
BACKGROUND: Brominated flame retardants (BFRs) are classified as important endocrine disruptors and persistent organic pollutants; nevertheless, there is no comprehensive investigation to evaluate the association between BFRs and hyperuricemia, and t...
Adaptive DDoS detection mode in software-defined SIP-VoIP using transfer learning with boosted meta-learner.
PloS one
Jun 26, 2025
The Internet has continued to provision its infrastructure as a platform for competitive marketing, enhanced productivity, and monetization efficacy. However, it has become a means for adversaries to exploit unsuspecting users and, in turn, compromis...
Exploring the relationship between graft dysfunction with serum metabolites and inflammatory proteins: integrating Mendelian randomization, single-cell analysis, machine learning, and SHAP methods for comprehensive analysis.
Renal failure
Jun 25, 2025
BACKGROUND: The exact mechanism of graft dysfunction has not been fully clarified. We aimed to explore the causal effects of serum metabolites on graft dysfunction and the mediating role of inflammatory proteins.
Predicting complications in breast reconstruction: External validation of a machine learning model.
Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Jun 25, 2025
BACKGROUND: Nipple-sparing mastectomy (NSM) with immediate implant-based breast reconstruction provides aesthetic and psychosocial benefits, but nipple-areolar complex (NAC) necrosis remains a significant risk. This study externally validated a previ...
A hybrid multi-instance learning-based identification of gastric adenocarcinoma differentiation on whole-slide images.
Biomedical engineering online
Jun 25, 2025
OBJECTIVE: To investigate the potential of a hybrid multi-instance learning model (TGMIL) combining Transformer and graph attention networks for classifying gastric adenocarcinoma differentiation on whole-slide images (WSIs) without manual annotation...
Machine learning methods, applications and economic analysis to predict heart failure hospitalisation risk: a scoping review.
BMJ open
Jun 25, 2025
BACKGROUND: Machine Learning (ML) has been transformative in healthcare, enabling more precise diagnostics, personalised treatment regimens and enhanced patient care. In cardiology, ML plays a crucial role in risk prediction and patient stratificati...
Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data.
JMIR research protocols
Jun 25, 2025
BACKGROUND: Suicide in local jails occurs at a higher rate than in the general population, requiring improvements to risk screening methods. Current suicide risk screening practices in jails are insufficient: They are commonly not conducted using val...
Comprehensive analysis and experimental validation of BST1 as a novel diagnostic biomarker for pediatric sepsis using multiple machine learning algorithms.
European journal of pediatrics
Jun 25, 2025
Bone marrow stromal cell antigen-1 (BST1) expression is elevated in a variety of human diseases, but its relationship with pediatric sepsis is unclear. This study aimed to investigate the expression of BST1 in pediatric sepsis patients and its value ...
In-silico study of approved drugs as potential inhibitors against 3CLpro and other viral proteins of CoVID-19.
PloS one
Jun 25, 2025
The global pandemic, due to the emergence of COVID-19, has created a public health crisis. It has a huge morbidity rate that was never comprehended in the recent decades. Despite numerous efforts, potent antiviral drugs are lacking. Repurposing of dr...
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