AIMC Topic: Risk Assessment

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Alteration of the corpus callosum in patients with Alzheimer's disease: Deep learning-based assessment.

PloS one
BACKGROUND: Several studies have reported changes in the corpus callosum (CC) in Alzheimer's disease. However, the involved region differed according to the study population and study group. Using deep learning technology, we ensured accurate analysi...

A Framework for Using Real-World Data and Health Outcomes Modeling to Evaluate Machine Learning-Based Risk Prediction Models.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: We propose a framework of health outcomes modeling with dynamic decision making and real-world data (RWD) to evaluate the potential utility of novel risk prediction models in clinical practice. Lung transplant (LTx) referral decisions in ...

Risk Assessment and Determination of Factors That Cause the Development of Hyperinsulinemia in School-Age Adolescents.

Medicina (Kaunas, Lithuania)
: Hyperinsulinemia and insulin resistance are not synonymous; if the risk of developing insulin resistance in adolescents is monitored, they do not necessarily have hyperinsulinemia. It is considered a condition of pre-diabetes and represents a condi...

Unsupervised learning of cross-modal mappings in multi-omics data for survival stratification of gastric cancer.

Future oncology (London, England)
This study presents a survival stratification model based on multi-omics integration using bidirectional deep neural networks (BiDNNs) in gastric cancer. Based on the survival-related representation features yielded by BiDNNs through integrating tr...

Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning-Assisted Gland Analysis.

Cancer research
Prostate cancer treatment planning is largely dependent upon examination of core-needle biopsies. The microscopic architecture of the prostate glands forms the basis for prognostic grading by pathologists. Interpretation of these convoluted three-dim...

RespiraTox - Development of a QSAR model to predict human respiratory irritants.

Regulatory toxicology and pharmacology : RTP
Respiratory irritation is an important human health endpoint in chemical risk assessment. There are two established modes of action of respiratory irritation, 1) sensory irritation mediated by the interaction with sensory neurons, potentially stimula...

Unsupervised Learning for Automated Detection of Coronary Artery Disease Subgroups.

Journal of the American Heart Association
Background The promise of precision population health includes the ability to use robust patient data to tailor prevention and care to specific groups. Advanced analytics may allow for automated detection of clinically informative subgroups that acco...

An interpretable machine learning model based on a quick pre-screening system enables accurate deterioration risk prediction for COVID-19.

Scientific reports
A high-performing interpretable model is proposed to predict the risk of deterioration in coronavirus disease 2019 (COVID-19) patients. The model was developed using a cohort of 3028 patients diagnosed with COVID-19 and exhibiting common clinical sym...