AIMC Topic: Risk Assessment
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Development and Validation of a Novel Prediction Model for Hearing Loss From Cisplatin Chemotherapy.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
May 5, 2025
PURPOSE: Cisplatin treats many common tumors but causes permanent and debilitating hearing loss (HL). The objective of this study was to develop and externally validate a predictive model of HL in cisplatin-treated children and adolescent cancer surv...
Uncovering rare earth and precious metal in landfill-mined soil-like-fractions: distribution prediction, ecological risk and resource potential.
Environmental pollution (Barking, Essex : 1987)
May 5, 2025
The introduction of rare earth elements (REEs) and precious metals (PMs) containing wastes in aged landfills leads to a significant pollutant and resource potential. Against this backdrop, the accumulation of REEs and PMs in soil-like-fractions (SLF)...
Prediction of high-risk pregnancy based on machine learning algorithms.
Scientific reports
May 4, 2025
This study explores the application of machine learning algorithms in predicting high-risk pregnancy among expectant mothers, aiming to construct an efficient predictive model to improve maternal health management. The study is based on the maternal ...
Identifying emergency department patients at high risk for opioid overdose using natural language processing and machine learning.
Journal of substance use and addiction treatment
May 3, 2025
INTRODUCTION: Emergency departments (ED) are potential sites for identifying and treating individuals at high risk for opioid overdose. This study used machine learning (ML)-based models to predict opioid overdose death in the 12 months after an ED v...
Integrating SHAP analysis with machine learning to predict postpartum hemorrhage in vaginal births.
BMC pregnancy and childbirth
May 3, 2025
OBJECTIVE: This study aimed to develop a machine learning (ML) model integrated with SHapley Additive exPlanations (SHAP) analysis to predict postpartum hemorrhage (PPH) following vaginal deliveries, offering a potential tool for personalized risk as...
A predictive framework using advanced machine learning approaches for measuring and analyzing the impact of synthetic agrochemicals on human health.
Scientific reports
May 3, 2025
Pesticides and other synthetic agrochemicals play a critical role in emerging agricultural practices by enhancing crop productivity and protecting against pests and diseases. However, their widespread application has raised significant concerns about...
Artificial intelligence for early detection of lung cancer in GPs' clinical notes: a retrospective observational cohort study.
The British journal of general practice : the journal of the Royal College of General Practitioners
May 2, 2025
BACKGROUND: The journey of >80% of patients diagnosed with lung cancer starts in general practice. About 75% of patients are diagnosed when it is at an advanced stage (3 or 4), leading to >80% mortality within 1 year at present. The long-term data in...
Predictive survival modelings for HIV-related cryptococcosis: comparing machine learning approaches.
Frontiers in cellular and infection microbiology
May 2, 2025
INTRODUCTION: HIV-associated cryptococcosis is marked by unpredictable disease trajectories and persistently high mortality rates worldwide. Although improved risk stratification and tailored clinical management are urgently needed to enhance patient...
Traffic accident risk prediction based on deep learning and spatiotemporal features of vehicle trajectories.
PloS one
May 2, 2025
With the acceleration of urbanization and the increase in traffic volume, frequent traffic accidents have significantly impacted public safety and socio-economic conditions. Traditional methods for predicting traffic accidents often overlook spatiote...
Machine Learning for Predicting Critical Events Among Hospitalized Children.
JAMA network open
May 1, 2025
IMPORTANCE: Unrecognized deterioration among hospitalized children is associated with a high risk of mortality and morbidity. The current approach to pediatric risk stratification is fragmented, as each hospital unit (emergency, ward, or intensive ca...
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