AIMC Topic: Risk Assessment
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Nontarget Screening Analysis Combined with Computational Toxicology: A Promising Solution for Identification and Risk Assessment of Environmental Pollutants in the Big Data Era.
Environmental science & technology
Jul 15, 2025
Synthetic chemicals are intensively utilized in modern societies, and their mixtures pose significant health and ecological threats. Nontarget screening (NTS) analysis allows for the simultaneous chemical identification and quantitative reporting of ...
Development and external validation of a machine learning model for predicting drug-induced immune thrombocytopenia in a real-world hospital cohort.
BMC medical informatics and decision making
Jul 15, 2025
BACKGROUND: Drug-induced immune thrombocytopenia (DITP) is a rare but potentially life-threatening adverse drug reaction, often underrecognized due to its nonspecific presentation and the lack of real-time diagnostic tools. Early identification of at...
Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP.
BMC medical informatics and decision making
Jul 15, 2025
BACKGROUND: Hemorrhage is a prevalent and critical condition in the intensive care unit (ICU), characterized by high incidence, elevated mortality rates, and substantial therapeutic challenges. Accurate prediction of mortality in patients with hemorr...
Predicting patient risk of leaving without being seen using machine learning: a retrospective study in a single overcrowded emergency department.
BMC emergency medicine
Jul 15, 2025
Emergency department (ED) overcrowding has become a critical issue in hospital management, leading to increased patient wait times and higher rates of individuals leaving without being seen (LWBS). This study aims to identify key factors influencing ...
Machine learning survival models for Non-alcoholic fatty liver disease based on a health checkup cohort.
BMC gastroenterology
Jul 15, 2025
OBJECTIVES: This study aimed to develop an accurate prediction model for the risk of Non-alcoholic fatty liver disease (NAFLD) using the random survival forests (RSF), and to investigate the distribution of NAFLD risk with time.
Predicting Morbidity and Mortality After Transjugular Intrahepatic Portosystemic Shunt Placement: A Review of Existing Models and Future Directions.
Techniques in vascular and interventional radiology
Jul 14, 2025
Transjugular intrahepatic portosystemic shunt (TIPS) is a key therapeutic intervention in the management of portal hypertension and its complications, such as variceal bleeding, hepatic hydrothorax, and refractory ascites. TIPS has historically been ...
Multimodal Deep Learning Model Based on Ultrasound and Cytological Images Predicts Risk Stratification of cN0 Papillary Thyroid Carcinoma.
Academic radiology
Jul 14, 2025
BACKGROUND: Accurately assessing the risk stratification of cN0 papillary thyroid carcinoma (PTC) preoperatively aids in making treatment decisions. We integrated preoperative ultrasound and cytological images of patients to develop and validate a mu...
Mortality and antibiotic timing in deep learning-derived surviving sepsis campaign risk groups: a multicenter study.
Critical care (London, England)
Jul 14, 2025
BACKGROUND: The current Surviving Sepsis Campaign (SSC) guidelines provide recommendations on timing of administering antibiotics in sepsis patients based on probability of sepsis and presence of shock. However, there have been minimal efforts to str...
Distribution mapping and risk assessment of lead in topsoil across the Tibetan Plateau.
Ecotoxicology and environmental safety
Jul 12, 2025
Lead exposure poses substantial long-term health risks, accounting for over 900,000 annual deaths worldwide and impairing cognitive development in more than 800 million children. Recent studies have indicated elevated soil lead contamination levels o...
Prediction of gastrointestinal hemorrhage in cardiology inpatients using an interpretable XGBoost model.
Scientific reports
Jul 12, 2025
Gastrointestinal bleeding (GIB) occurs more frequently in cardiovascular patients than in the general population, significantly affecting morbidity and mortality. However, existing predictive models often lack sufficient accuracy and interpretability...
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