AIMC Topic: Workflow
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Optimization of Radiology Workflow with Artificial Intelligence.
Radiologic clinics of North America
Nov 1, 2021
The potential of artificial intelligence (AI) in radiology goes far beyond image analysis. AI can be used to optimize all steps of the radiology workflow by supporting a variety of nondiagnostic tasks, including order entry support, patient schedulin...
Implementing FAIR data management within the German Network for Bioinformatics Infrastructure (de.NBI) exemplified by selected use cases.
Briefings in bioinformatics
Sep 2, 2021
This article describes some use case studies and self-assessments of FAIR status of de.NBI services to illustrate the challenges and requirements for the definition of the needs of adhering to the FAIR (findable, accessible, interoperable and reusabl...
Gaps in standards for integrating artificial intelligence technologies into ophthalmic practice.
Current opinion in ophthalmology
Sep 1, 2021
PURPOSE OF REVIEW: The purpose of this review is to provide an overview of healthcare standards and their relevance to multiple ophthalmic workflows, with a specific emphasis on describing gaps in standards development needed for improved integration...
Multiplex computational pathology for treatment response predication.
Cancer cell
Aug 9, 2021
Recently published in Science, AstroPath outlines a standardized workflow for multiplex immunofluorescence (mIF) panel development, imaging, and analysis; showcases its potential in biomarker discovery for predicting response to anti-PD-1 treatment; ...
Vaxign2: the second generation of the first Web-based vaccine design program using reverse vaccinology and machine learning.
Nucleic acids research
Jul 2, 2021
Vaccination is one of the most significant inventions in medicine. Reverse vaccinology (RV) is a state-of-the-art technique to predict vaccine candidates from pathogen's genome(s). To promote vaccine development, we updated Vaxign2, the first web-bas...
Machine learning in health care and laboratory medicine: General overview of supervised learning and Auto-ML.
International journal of laboratory hematology
Jul 1, 2021
Artificial Intelligence (AI) and machine learning (ML) have now spawned a new field within health care and health science research. These new predictive analytics tools are starting to change various facets of our clinical care domains including the ...
Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning.
Journal of the American Medical Informatics Association : JAMIA
Jun 12, 2021
OBJECTIVE: The characteristics of clinician activities while interacting with electronic health record (EHR) systems can influence the time spent in EHRs and workload. This study aims to characterize EHR activities as tasks and define novel, data-dri...
Consolidated EHR Workflow for Endoscopy Quality Reporting.
Studies in health technology and informatics
May 27, 2021
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
Apr 1, 2021
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
Mar 2, 2021
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...
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