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Workflow

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Consolidated EHR Workflow for Endoscopy Quality Reporting.

Studies in health technology and informatics
Although colonoscopy is the most frequently performed endoscopic procedure, the lack of standardized reporting is impeding clinical and translational research. Inadequacies in data extraction from the raw, unstructured text in electronic health recor...

Machine Learning for Surgical Phase Recognition: A Systematic Review.

Annals of surgery
OBJECTIVE: To provide an overview of ML models and data streams utilized for automated surgical phase recognition.

A machine-learning approach to map landscape connectivity in with genetic and environmental data.

Proceedings of the National Academy of Sciences of the United States of America
Mapping landscape connectivity is important for controlling invasive species and disease vectors. Current landscape genetics methods are often constrained by the subjectivity of creating resistance surfaces and the difficulty of working with interact...

Application of artificial intelligence in gastroenterology: Potential role in clinical practice.

Journal of gastroenterology and hepatology
Artificial intelligence (AI) based on deep learning boosted medical research in the past years and is expected to enormously change the style of health care in many aspects in the foreseeable future. Nowadays, there are exploding volumes of healthcar...

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

JAMA psychiatry
IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to yo...

Tool recommender system in Galaxy using deep learning.

GigaScience
BACKGROUND: Galaxy is a web-based and open-source scientific data-processing platform. Researchers compose pipelines in Galaxy to analyse scientific data. These pipelines, also known as workflows, can be complex and difficult to create from thousands...

[Artificial intelligence in oncological radiology : A (p)review].

Der Radiologe
BACKGROUND: Artificial intelligence (AI) has the potential to fundamentally change medicine within the coming decades. Radiological imaging is one of the primary fields of its clinical application.

NEURO-LEARN: a Solution for Collaborative Pattern Analysis of Neuroimaging Data.

Neuroinformatics
The development of neuroimaging instrumentation has boosted neuroscience researches. Consequently, both the fineness and the cost of data acquisition have profoundly increased, leading to the main bottleneck of this field: limited sample size and hig...