AIMC Topic: Risk Assessment

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QSAR Model Development for the Environmental Risk Limits and High-Risk List Identification of Phenylurea Herbicides in Aquatic Environments.

Journal of agricultural and food chemistry
Due to the extensive residues of phenylurea herbicides (PUHs) in the environment, it is important for the ecological risk assessment of PUHs to determine their environmental risk limits and identify the high-risk PUHs. This study derived the environm...

Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease.

Italian journal of pediatrics
BACKGROUND: Kawasaki disease (KD) is a leading cause of acquired heart disease in children that is treated with intravenous immunoglobulin (IVIG). However, 10-20% of cases exhibit IVIG resistance, which increases the risk of coronary complications. E...

Diagnostic accuracy of radiomics in risk stratification of gastrointestinal stromal tumors: A systematic review and meta-analysis.

European journal of radiology
RATIONALE AND OBJECTIVES: This systematic review and meta-analysis aimed to assess the diagnostic accuracy of radiomics in risk stratification of gastrointestinal stromal tumors (GISTs). It focused on evaluating radiomic models as a non-invasive tool...

Regulatory practices on the genotoxicity testing of nanomaterials and outlook for the future.

Regulatory toxicology and pharmacology : RTP
The toxicity of nanomaterials(NMs) is closely tied to their physicochemical properties, such as size, shape, surface chemistry, stability in biological medium, and state of agglomeration as well to their uptake by cells. Key deficiencies in standardi...

Plasma proteomic profiles for early detection and risk stratification of non-small cell lung carcinoma: A prospective cohort study with 52,913 participants.

International journal of cancer
Early detection of non-small cell lung cancer (NSCLC) can improve survival rates, and plasma proteomics may provide effective tools for risk prediction. The population for this study included 52,913 participants and 2911 plasma proteomics from UK Bio...

Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.

BMC medical informatics and decision making
The rapid decline of kidney function in middle-aged and elderly people has become an increasingly serious public health problem. Machine learning (ML) technology has substantial potential to disease prediction. The present study use dataset from the ...

Towards prehospital risk stratification using deep learning for ECG interpretation in suspected acute coronary syndrome.

BMJ health & care informatics
OBJECTIVES: Most patients presenting with chest pain in the emergency medical services (EMS) setting are suspected of non-ST-elevation acute coronary syndrome (NSTE-ACS). Distinguishing true NSTE-ACS from non-cardiac chest pain based solely on the EC...

Preliminary analysis of AI-based thyroid nodule evaluation in a non-subspecialist endocrinology setting.

Endocrine
PURPOSE: Thyroid nodules are commonly evaluated using ultrasound-based risk stratification systems, which rely on subjective descriptors. Artificial intelligence (AI) may improve assessment, but its effectiveness in non-subspecialist settings is uncl...

Urban-rural inequality in soil heavy metal health risks: Insights from Baoding, China.

Ecotoxicology and environmental safety
Soil heavy metal contamination poses serious health risks, but few studies have quantitatively assessed disparities in these risks between urban and rural populations. To address this gap, we introduce a novel framework integrating machine learning a...