Application of machine learning models for predicting risk factors of acute exacerbations in chronic obstructive pulmonary disease. [PDF]
Kuang D +5 more
europepmc +1 more source
ABSTRACT Food insecurity remains a persistent challenge in rural Colombia, driven by structural inequalities, livelihood constraints and exposure to shocks. This paper examined the determinants and predictive drivers of household food insecurity using nationally representative data from the Food and Agriculture Organisation (FAO) Data in Emergencies ...
Adrino Mazenda
wiley +1 more source
AI Characterisation of Discordance Profiles Between Stress Electrocardiogram and Myocardial Tomoscintigraphy Using Random Forest XGBoost and SHAP. [PDF]
El Maadaoui Y +3 more
europepmc +1 more source
Intelligent design of artificial biocatalyst for biomedical diseases
This review summarizes recent advances in the intelligent design of artificial biocatalysts for biomedical diseases. By leveraging tailored design strategies, including environmentāresponsive engineering and rational/artificial intelligenceāaided optimization, these biocatalysts enable precise modulation of pathological microenvironments and targeted ...
Lijie Zhang +3 more
wiley +1 more source
Evaluating comorbidity scoring systems for flumatinib therapy in chronic myeloid leukemia: a machine learning and SHAP-based predictive analysis. [PDF]
Yang Y, Li Y, Wang J.
europepmc +1 more source
Empowering Prediction of Resting Energy Expenditure in Free-Living Settings by AI Tools: Application of a Population-Specific Equation from Saudi Arabia. [PDF]
Almuhtadi Y +4 more
europepmc +1 more source
Prediction of polycystic ovary syndrome using machine learning models: Addressing class imbalance and high dimensionality. [PDF]
Acharya S, Poojari S, Kamath A.
europepmc +1 more source
Explainable Machine Learning for Early Prediction of Surgical Necessity in Gastrointestinal Emergencies: A Multimodal Diagnostic Study. [PDF]
Anca Monica OM +9 more
europepmc +1 more source
A robust multi-location evaluation of a machine learning framework for wind power forecasting. [PDF]
Ali U +7 more
europepmc +1 more source

