AIMC Topic: Quality Assurance, Health Care

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A mathematical framework for virtual IMRT QA using machine learning.

Medical physics Jul 1, 2016
PURPOSE: It is common practice to perform patient-specific pretreatment verifications to the clinical delivery of IMRT. This process can be time-consuming and not altogether instructive due to the myriad sources that may produce a failing result. The...
Humans Machine Learning Neoplasms Regression Analysis Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care Radiotherapy Dosage Radiotherapy, Intensity-Modulated Treatment Failure Radiometry
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Assessment of quality outcomes for robotic pancreaticoduodenectomy: identification of the learning curve.

JAMA surgery May 1, 2015
IMPORTANCE: Quality assessment is an important instrument to ensure optimal surgical outcomes, particularly during the adoption of new surgical technology. The use of the robotic platform for complex pancreatic resections, such as the pancreaticoduod...
Humans Retrospective Studies Female Aged Male Middle Aged Pancreatic Neoplasms Education, Medical, Continuing Robotics Quality Assurance, Health Care Pancreaticoduodenectomy Learning Curve
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Challenges of minimally invasive pancreas surgery growth with such a high learning curve.

JAMA surgery May 1, 2015
Humans Female Male Pancreatic Neoplasms Education, Medical, Continuing Robotics Quality Assurance, Health Care Pancreaticoduodenectomy Learning Curve
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Utility of Arden Syntax for Representation of Fuzzy Logic in Clinical Quality Measures.

Studies in health technology and informatics Jan 1, 2015
BACKGROUND: Prior work has established that fuzzy logic is prevalent in clinical practice guidelines and that Arden Syntax is suitable for representing clinical quality measures (CQMs). Approved since then, Arden Syntax v2.9 (2012) has formal constru...
Software Decision Support Systems, Clinical Fuzzy Logic Natural Language Processing Quality Assurance, Health Care Quality Indicators, Health Care Semantics Terminology as Topic California
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Assessment of an expert system for the automated validation of electrophoretic profiles.

Clinical laboratory Jan 1, 2015
BACKGROUND: The Core-lab of the Greater Romagna Area Hub Laboratory carries out about 250,000 capillary electrophoresis assays/year. The huge workload demands the assessing of an Experimental Expert System (EES) capable to sort out the negative sampl...
Neural Networks, Computer Electrophoresis, Capillary Expert Systems Quality Assurance, Health Care
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