AI Medical Compendium Topic:
Risk Assessment

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Predicting 1 year readmission for heart failure: A comparative study of machine learning and the LACE index.

ESC heart failure
AIMS: There is a lack of tools for accurately identifying the risk of readmission for heart failure in elderly patients with arrhythmia. The aim of this study was to establish and compare the performance of the LACE [length of stay ('L'), acute (emer...

Construction of an antidepressant priority list based on functional, environmental, and health risks using an interpretable mixup-transformer deep learning model.

Journal of hazardous materials
As emerging pollutants, antidepressants (AD) must be urgently investigated for risk identification and assessment. This study constructed a comprehensive-effect risk-priority screening system (ADRank) for ADs by characterizing AD functionality, occur...

Machine learning models for predicting early hemorrhage progression in traumatic brain injury.

Scientific reports
This study explores the progression of intracerebral hemorrhage (ICH) in patients with mild to moderate traumatic brain injury (TBI). It aims to predict the risk of ICH progression using initial CT scans and identify clinical factors associated with ...

Hepatic toxicity prediction of bisphenol analogs by machine learning strategy.

The Science of the total environment
Toxicological studies have demonstrated the hepatic toxicity of several bisphenol analogs (BPs), a prevalent type of endocrine disruptor. The development of Adverse Outcome Pathway (AOP) has substantially contributed to the rapid risk assessment for ...

Towards proactive palliative care in oncology: developing an explainable EHR-based machine learning model for mortality risk prediction.

BMC palliative care
BACKGROUND: Ex-ante identification of the last year in life facilitates a proactive palliative approach. Machine learning models trained on electronic health records (EHR) demonstrate promising performance in cancer prognostication. However, gaps in ...

A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability.

Acta tropica
The post-effects of the COronaVIrus Disease (COVID-19) vary depending on socioeconomic and biological factors. Similarly, the effects of vaccination on people's immunity vary across several factors. After the pandemic, real-life post-vaccination anom...

A deep learning approach to explore the association of age-related macular degeneration polygenic risk score with retinal optical coherence tomography: A preliminary study.

Acta ophthalmologica
PURPOSE: Age-related macular degeneration (AMD) is a complex eye disorder affecting millions worldwide. This article uses deep learning techniques to investigate the relationship between AMD, genetics and optical coherence tomography (OCT) scans.

Risk prediction models of depression in older adults with chronic diseases.

Journal of affective disorders
BACKGROUND: Detecting potential depression and identifying the critical predictors of depression among older adults with chronic diseases are essential for timely intervention and management of depression. Therefore, risk prediction models (RPMs) of ...

A novel support vector machine-based 1-day, single-dose prediction model of genotoxic hepatocarcinogenicity in rats.

Archives of toxicology
The development of a rapid and accurate model for determining the genotoxicity and carcinogenicity of chemicals is crucial for effective cancer risk assessment. This study aims to develop a 1-day, single-dose model for identifying genotoxic hepatocar...

AI-enhanced integration of genetic and medical imaging data for risk assessment of Type 2 diabetes.

Nature communications
Type 2 diabetes (T2D) presents a formidable global health challenge, highlighted by its escalating prevalence, underscoring the critical need for precision health strategies and early detection initiatives. Leveraging artificial intelligence, particu...