AI Medical Compendium Topic

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Workflow Applications of Artificial Intelligence in Radiology and an Overview of Available Tools.

Journal of the American College of Radiology : JACR
In the past decade, there has been tremendous interest in applying artificial intelligence (AI) to improve the field of radiology. Currently, numerous AI applications are in development, with potential benefits spanning all steps of the imaging chain...

Artificial Intelligence Applications for Workflow, Process Optimization and Predictive Analytics.

Neuroimaging clinics of North America
There is great potential for artificial intelligence (AI) applications, especially machine learning and natural language processing, in medical imaging. Much attention has been garnered by the image analysis tasks for diagnostic decision support and ...

Assessing the Anti-cancer Therapeutic Mechanism of a Herbal Combination for Breast Cancer on System-level by a Network Pharmacological Approach.

Anticancer research
BACKGROUND/AIM: Accumulating evidence has shown therapeutic effects of herbals on breast cancer, a commonly diagnosed malignancy in women worldwide. However, their underlying mechanisms remain unclear. We aimed to explore the mode of action of a rece...

Artificial Intelligence and Machine Learning in Radiology: Current State and Considerations for Routine Clinical Implementation.

Investigative radiology
Although artificial intelligence (AI) has been a focus of medical research for decades, in the last decade, the field of radiology has seen tremendous innovation and also public focus due to development and application of machine-learning techniques ...

Ethical considerations for artificial intelligence: an overview of the current radiology landscape.

Diagnostic and interventional radiology (Ankara, Turkey)
Artificial intelligence (AI) has great potential to accelerate scientific discovery in medicine and to transform healthcare. In radiology, AI is about to enter into clinical practice and has a wide range of applications covering the whole diagnostic ...

Risk prediction of delirium in hospitalized patients using machine learning: An implementation and prospective evaluation study.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Machine learning models trained on electronic health records have achieved high prognostic accuracy in test datasets, but little is known about their embedding into clinical workflows. We implemented a random forest-based algorithm to iden...

A New Classification of Benign, Premalignant, and Malignant Endometrial Tissues Using Machine Learning Applied to 1413 Candidate Variables.

International journal of gynecological pathology : official journal of the International Society of Gynecological Pathologists
Benign normal (NL), premalignant (endometrial intraepithelial neoplasia, EIN) and malignant (cancer, EMCA) endometria must be precisely distinguished for optimal management. EIN was objectively defined previously as a regression model incorporating m...

GlyGen data model and processing workflow.

Bioinformatics (Oxford, England)
SUMMARY: Glycoinformatics plays a major role in glycobiology research, and the development of a comprehensive glycoinformatics knowledgebase is critical. This application note describes the GlyGen data model, processing workflow and the data access i...