AI Medical Compendium Topic:
Decision Support Systems, Clinical

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Development of a periodontitis risk assessment model for primary care providers in an interdisciplinary setting.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2020
BACKGROUND: Periodontitis (PD), a form of gum disease, is a major public health concern as it is globally prevalent and harms both individual quality of life and economic productivity. Global cost in lost productivity is estimated at US$54 billion an...
Primary Health Care Decision Support Systems, Clinical Logistic Models Socioeconomic Factors Adult Male Middle Aged Comorbidity Blood Pressure Bayes Theorem Sex Factors Body Weights and Measures Oral Hygiene Support Vector Machine Age Factors Lipids Periodontitis Humans Aged Neural Networks, Computer Aged, 80 and over Retrospective Studies Artificial Intelligence Young Adult Female
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Addressing Bias in Artificial Intelligence in Health Care.

JAMA Dec 24, 2019
Bias Artificial Intelligence Algorithms Delivery of Health Care Decision Support Systems, Clinical Humans
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High Accuracy of Convolutional Neural Network for Evaluation of Helicobacter pylori Infection Based on Endoscopic Images: Preliminary Experience.

Clinical and translational gastroenterology Dec 1, 2019
OBJECTIVES: Application of artificial intelligence in gastrointestinal endoscopy is increasing. The aim of the study was to examine the accuracy of convolutional neural network (CNN) using endoscopic images for evaluating Helicobacter pylori (H. pylo...
Biopsy Endoscopy, Gastrointestinal Helicobacter Infections Helicobacter pylori Breath Tests Carbon Isotopes Gastroscopy Gastric Mucosa Pilot Projects ROC Curve Decision Support Systems, Clinical Image Processing, Computer-Assisted Adult Male Middle Aged Deep Learning Humans Retrospective Studies Female
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Predicting emergency department orders with multilabel machine learning techniques and simulating effects on length of stay.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: Emergency departments (EDs) continue to pursue optimal patient flow without sacrificing quality of care. The speed with which a healthcare provider receives pertinent information, such as results from clinical orders, can impact flow. We s...
Humans Machine Learning Length of Stay Practice Patterns, Physicians' Decision Support Systems, Clinical Emergency Service, Hospital Benchmarking Diagnostic Tests, Routine
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Reducing drug prescription errors and adverse drug events by application of a probabilistic, machine-learning based clinical decision support system in an inpatient setting.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
BACKGROUND: Drug prescription errors are made, worldwide, on a daily basis, resulting in a high burden of morbidity and mortality. Existing rule-based systems for prevention of such errors are unsuccessful and associated with substantial burden of fa...
Humans Machine Learning Algorithms Patient Safety Medical Order Entry Systems Academic Medical Centers Prospective Studies Medication Errors Decision Support Systems, Clinical Drug Therapy, Computer-Assisted Drug-Related Side Effects and Adverse Reactions Medication Systems, Hospital Israel
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An FP's guide to AI-enabled clinical decision support.

The Journal of family practice Nov 1, 2019
To better understand the capabilities and challenges of artificial intelligence and machine learning, we look at the role they can play in screening for retinopathy and colon cancer.
Sensitivity and Specificity Colonoscopy Decision Support Systems, Clinical Early Detection of Cancer Neural Networks, Computer Colonic Neoplasms Humans Artificial Intelligence Retinal Diseases Machine Learning Family Practice Clinical Decision-Making
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Explainable Artificial Intelligence for Safe Intraoperative Decision Support.

JAMA surgery Nov 1, 2019
Artificial Intelligence Intraoperative Care Risk Assessment Intraoperative Complications Decision Support Systems, Clinical Diffusion of Innovation Inventions Humans
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A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.

Critical care medicine Nov 1, 2019
OBJECTIVES: Develop and implement a machine learning algorithm to predict severe sepsis and septic shock and evaluate the impact on clinical practice and patient outcomes.
Diagnosis, Computer-Assisted Sepsis Cohort Studies Decision Support Systems, Clinical Hospitals, Teaching Shock, Septic Text Messaging Algorithms Retrospective Studies Electronic Health Records Humans Sensitivity and Specificity Machine Learning
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Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

Critical care medicine Nov 1, 2019
OBJECTIVE: To assess clinician perceptions of a machine learning-based early warning system to predict severe sepsis and septic shock (Early Warning System 2.0).
Humans Machine Learning Practice Patterns, Physicians' Attitude of Health Personnel Practice Patterns, Nurses' Text Messaging Algorithms Sepsis Hospitals, Teaching Nursing Staff, Hospital Prospective Studies Decision Support Systems, Clinical Medical Staff, Hospital Electronic Health Records Shock, Septic Diagnosis, Computer-Assisted
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Natural Language Processing Approaches to Detect the Timeline of Metastatic Recurrence of Breast Cancer.

JCO clinical cancer informatics Oct 1, 2019
PURPOSE: Electronic medical records (EMRs) and population-based cancer registries contain information on cancer outcomes and treatment, yet rarely capture information on the timing of metastatic cancer recurrence, which is essential to understand can...
Time Factors Aged Medical Informatics Decision Support Systems, Clinical Registries California Follow-Up Studies Humans Neoplasm Recurrence, Local Adult Natural Language Processing Algorithms Breast Neoplasms Databases, Factual Middle Aged Female
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