AI Medical Compendium Topic

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Models, Statistical

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A machine learning and network framework to discover new indications for small molecules.

PLoS computational biology
Drug repurposing, identifying novel indications for drugs, bypasses common drug development pitfalls to ultimately deliver therapies to patients faster. However, most repurposing discoveries have been led by anecdotal observations (e.g. Viagra) or ex...

Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury.

JAMA network open
IMPORTANCE: Acute kidney injury (AKI) is associated with increased morbidity and mortality in hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and few prediction models have been externally validated.

Development of prognostic model for patients at CKD stage 3a and 3b in South Central China using computational intelligence.

Clinical and experimental nephrology
BACKGROUND: Chronic kidney disease (CKD) stage 3 was divided into two subgroups by eGFR (45 mL/ min 1.73 m). There is difference in prevalence of CKD, racial differences, economic development, genetic, and environmental backgrounds between China and ...

Prediction of the development of acute kidney injury following cardiac surgery by machine learning.

Critical care (London, England)
BACKGROUND: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in increased morbidity and mortality after cardiac surgery. Most established prediction models are limited to the analysis of nonlinear relation...

Validation of the usefulness of artificial neural networks for risk prediction of adverse drug reactions used for individual patients in clinical practice.

PloS one
Artificial neural networks are the main tools for data mining and were inspired by the human brain and nervous system. Studies have demonstrated their usefulness in medicine. However, no studies have used artificial neural networks for the prediction...

Machine learning outcome regression improves doubly robust estimation of average causal effects.

Pharmacoepidemiology and drug safety
BACKGROUND: Doubly robust estimation produces an unbiased estimator for the average treatment effect unless both propensity score (PS) and outcome models are incorrectly specified. Studies have shown that the doubly robust estimator is subject to mor...

Machine learning for modeling animal movement.

PloS one
Animal movement drives important ecological processes such as migration and the spread of infectious disease. Current approaches to modeling animal tracking data focus on parametric models used to understand environmental effects on movement behavior...

BIOINTMED: integrated biomedical knowledge base with ontologies and clinical trials.

Medical & biological engineering & computing
Biomedical data are complex and heterogeneous. An ample reliable quantity of data is important for understanding and exploring the domain. The work aims to integrate biomedical data from various heterogeneous sources like dictionaries or corpus and a...

DNC4mC-Deep: Identification and Analysis of DNA N4-Methylcytosine Sites Based on Different Encoding Schemes By Using Deep Learning.

Cells
N4-methylcytosine as one kind of modification of DNA has a critical role which alters genetic performance such as protein interactions, conformation, stability in DNA as well as the regulation of gene expression same cell developmental and genomic im...