AI Medical Compendium Topic:
Predictive Value of Tests

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Rapid whole-heart CMR with single volume super-resolution.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Three-dimensional, whole heart, balanced steady state free precession (WH-bSSFP) sequences provide delineation of intra-cardiac and vascular anatomy. However, they have long acquisition times. Here, we propose significant speed-ups using ...

A Transparent and Adaptable Method to Extract Colonoscopy and Pathology Data Using Natural Language Processing.

Journal of medical systems
Key variables recorded as text in colonoscopy and pathology reports have been extracted using natural language processing (NLP) tools that were not easily adaptable to new settings. We aimed to develop a reliable NLP tool with broad adaptability. Dur...

Soft Tissue Sarcoma: Preoperative MRI-Based Radiomics and Machine Learning May Be Accurate Predictors of Histopathologic Grade.

AJR. American journal of roentgenology
The purpose of this study was to assess the value of radiomics features for differentiating soft tissue sarcomas (STSs) of different histopathologic grades. The T1-weighted and fat-suppressed T2-weighted MR images of 70 STSs of varying grades (35 l...

Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band imaging.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Magnifying endoscopy with narrow-band imaging (ME-NBI) has made a huge contribution to clinical practice. However, acquiring skill at ME-NBI diagnosis of early gastric cancer (EGC) requires considerable expertise and experience. R...

Machine Learning for Brain Stroke: A Review.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful tool in health settings, offering personalized clinical care for stroke patients. An application of ML and Deep Learning in health care is growing ho...

Prediction of 1-Year Mortality from Acute Myocardial Infarction Using Machine Learning.

The American journal of cardiology
Risk stratification at hospital discharge could be instrumental in guiding postdischarge care. In this study, the risk models for 1-year mortality using machine learning (ML) were evaluated for guiding management of acute myocardial infarction (AMI) ...

Predicting In Vitro Neurotoxicity Induced by Nanoparticles Using Machine Learning.

International journal of molecular sciences
The practice of non-testing approaches in nanoparticles hazard assessment is necessary to identify and classify potential risks in a cost effective and timely manner. Machine learning techniques have been applied in the field of nanotoxicology with e...

Strategies for Testing Intervention Matching Schemes in Cancer.

Clinical pharmacology and therapeutics
Personalized medicine, or the tailoring of health interventions to an individual's nuanced and often unique genetic, biochemical, physiological, behavioral, and/or exposure profile, is seen by many as a biological necessity given the great heterogene...