AIMC Topic: Quality Improvement
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De novo Nanopore read quality improvement using deep learning.
BMC bioinformatics
Nov 6, 2019
BACKGROUND: Long read sequencing technologies such as Oxford Nanopore can greatly decrease the complexity of de novo genome assembly and large structural variation identification. Currently Nanopore reads have high error rates, and the errors often c...
Identification of postoperative complications using electronic health record data and machine learning.
American journal of surgery
Oct 9, 2019
BACKGROUND: Using the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) complication status of patients who underwent an operation at the University of Colorado Hospital, we developed a machine learning algorithm for ...
Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfaces.
International journal of medical informatics
Sep 27, 2019
OBJECTIVES: To determine the effect of a domain-specific ontology and machine learning-driven user interfaces on the efficiency and quality of documentation of presenting problems (chief complaints) in the emergency department (ED).
Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice.
Clinical radiology
Sep 11, 2019
AIM: To test the diagnostic performance of a deep learning-based system for the detection of clinically significant pulmonary nodules/masses on chest radiographs.
Humans
Software
Algorithms
Male
Middle Aged
Diagnosis, Computer-Assisted
Deep Learning
Retrospective Studies
Tomography, X-Ray Computed
Female
Sensitivity and Specificity
Lung Neoplasms
Taiwan
Multiple Pulmonary Nodules
Radiographic Image Interpretation, Computer-Assisted
Solitary Pulmonary Nodule
Quality Improvement
Radiography, Thoracic
Artificial Intelligence in Nephrology: Core Concepts, Clinical Applications, and Perspectives.
American journal of kidney diseases : the official journal of the National Kidney Foundation
Aug 23, 2019
Artificial intelligence is playing an increasingly important role in many fields of medicine, assisting physicians in most steps of patient management. In nephrology, artificial intelligence can already be used to improve clinical care, hemodialysis ...
Predicting Outpatient Appointment Demand Using Machine Learning and Traditional Methods.
Journal of medical systems
Jul 19, 2019
Traditional methods have long been used for clinical demand forecasting. Machine learning methods represent the next evolution in forecasting, but model choice and optimization remain challenging for achieving optimal results. To determine the best m...
Children's Fear and Pain During Medical Procedures: A Quality Improvement Study With a Humanoid Robot.
The Canadian journal of nursing research = Revue canadienne de recherche en sciences infirmieres
Jul 18, 2019
BACKGROUND: Pediatric patients undergo a variety of painful medical procedures.
Clinical Documentation and Patient Care Using Artificial Intelligence in Radiation Oncology.
Journal of the American College of Radiology : JACR
Jun 22, 2019
Detailed clinical documentation is required in the patient-facing specialty of radiation oncology. The burden of clinical documentation has increased significantly with the introduction of electronic health records and participation in payer-mandated...
Feasibility of Natural Language Processing-Assisted Auditing of Critical Findings in Chest Radiology.
Journal of the American College of Radiology : JACR
Jun 21, 2019
OBJECTIVE: Time-sensitive communication of critical imaging findings like pneumothorax or pulmonary embolism to referring physicians is essential for patient safety. The definitive communication is the radiology free-text report. Quality assurance in...
Pilot Projects
United States
Natural Language Processing
Feasibility Studies
Female
Sensitivity and Specificity
Male
Radiography, Thoracic
Humans
Machine Learning
Quality Improvement
Research Design
Academic Medical Centers
Retrospective Studies
Automation
Tomography, X-Ray Computed
Radiology Information Systems
Deep-Learning Language-Modeling Approach for Automated, Personalized, and Iterative Radiology-Pathology Correlation.
Journal of the American College of Radiology : JACR
Jun 4, 2019
PURPOSE: Radiology-pathology correlation has long been foundational to continuing education, peer learning, quality assurance, and multidisciplinary patient care. The objective of this study was to determine whether modern deep-learning language-mode...
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