AIMC Topic: Risk Assessment

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Improving the Ecotoxicological Hazard Assessment of Chemicals by Pairwise Learning.

Environmental science & technology
This study demonstrates how machine learning techniques can bridge data gaps in the ecotoxicological hazard assessment of chemical pollutants and illustrates how the results can be used in practice. The innovation herein consists of the prediction of...

Heuristic Topological Graph Convolutional Network for Risk Prediction of Potentially Toxic Elements in Cultivated Soils.

Environmental science & technology
Contamination of cultivated soils with potentially toxic elements (PTEs) poses a growing threat to global food security. Although existing risk assessments have examined the accumulation and toxicity of PTEs, their dynamic interplay with multidimensi...

Machine Learning-Assisted Tissue-Residue-Based Risk Assessment for Protecting Threatened and Endangered Fishes in the Yangtze River Basin.

Environmental science & technology
Assessing pollutant risks to threatened and endangered (T&E) species is crucial for their conservation. However, traditional risk assessment methods for bioaccumulative pollutants to T&E fishes is challenging due to uncertainties in exposure-based to...

Assessing risk of groundwater pollution exposure from sea level rise in California.

The Science of the total environment
Sea level rise (SLR) will cause a groundwater table rise in coastal aquifers, and this can trigger exposure to toxic chemicals via direct contact with contaminated water or through vapor intrusion. This study presents deep learning- and explainable a...

Early Identification of Vitamin D Deficiency Risk Through Public Health Screening Data.

Studies in health technology and informatics
Metabolic syndrome, characterized by central obesity, hypertension, hyperglycemia, dyslipidemia, and reduced high-density lipoprotein levels, significantly increases the risk of cardiovascular diseases. Vitamin D, essential for calcium regulation and...

VaxPulse: Active Global Vaccine Infodemic Risk Assessment.

Studies in health technology and informatics
Vaccine infodemics, driven by misinformation, disinformation, and inauthentic online behaviours, pose significant threats to global public health. This paper presents our response to this challenge, demonstrating how we developed VaxPulse Vaccine Inf...

Development of Multivariable Prediction Models for 30-Day Risk of Readmission After COPD Hospital Admission: A Retrospective Cohort Study Using Electronic Medical Record Data from 7 Hospitals.

Studies in health technology and informatics
BACKGROUND: Approximately 20% of patients who are discharged from hospital for an acute exacerbation of COPD (AECOPD) are readmitted within 30 days. Prediction scores are helpful to identify those who are at higher risk of readmission, such that they...

Machine-Learning-Based Prediction of Suicide Risk Using Preliminary Questionnaire and Consultation Text.

Studies in health technology and informatics
In Japan, chat-based mental health counseling services have low response rates due to understaffing. In this article, machine learning (ML) based suicide risk classification methods are proposed. A dataset was constructed including a medical question...

Predicting Postpartum Depression Risk Using Social Determinants of Health.

Studies in health technology and informatics
Postpartum depression (PPD) affects approximately 20% of women after childbirth and has complex etiology. Existing predictive models of PPD lack training on large, national datasets and comprehensive integration of clinical and social determinants. T...

Predicting Nephrectomy Risk in Patients with Renal Cancer Using Real-World Electronic Health Records.

Studies in health technology and informatics
Nephrectomy, the surgical removal of a kidney, is a critical treatment for renal cancer, and predicting its likelihood can help guide clinical decision-making and optimize preoperative planning. This study utilized real-world electronic health record...