AIMC Topic: Machine Learning
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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.
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...
Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction.
PloS one
Jun 25, 2025
Precise forecasting of cancer outcomes is essential for medical professionals to assess the well-being of patients and develop customized therapeutic plans. Despite its importance, achieving precise forecasts remains a formidable challenge. To tackle...
Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.
PloS one
Jun 25, 2025
Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, current methods such as finger pricking and continuous glucose monitoring systems (CGMS) are invasive, ...
Statistical and machine learning models for predicting university dropout and scholarship impact.
PloS one
Jun 25, 2025
Although student dropout is an inevitable aspect of university enrollment, when analyzed, universities can gather information which enables them to take preventative actions that mitigate dropout risk. We study a data set consisting of 4,424 records ...
Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data.
PloS one
Jun 25, 2025
Population prediction could provide effective data support for social and economic planning and decision-making, especially for the sub-national population forecasting accurately. In addition to realizing efficient smart population management, this r...
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