AIMC Topic: Patient Acuity
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Automated grading of enlarged perivascular spaces in clinical imaging data of an acute stroke cohort using an interpretable, 3D deep learning framework.
Scientific reports
Jan 17, 2022
Enlarged perivascular spaces (EPVS), specifically in stroke patients, has been shown to strongly correlate with other measures of small vessel disease and cognitive impairment at 1 year follow-up. Typical grading of EPVS is often challenging and time...
Assessing the Economic Value of Clinical Artificial Intelligence: Challenges and Opportunities.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Oct 9, 2021
OBJECTIVES: Clinical artificial intelligence (AI) is a novel technology, and few economic evaluations have focused on it to date. Before its wider implementation, it is important to highlight the aspects of AI that challenge traditional health techno...
Chronic kidney disease diagnosis using decision tree algorithms.
BMC nephrology
Aug 9, 2021
BACKGROUND: Chronic Kidney Disease (CKD), i.e., gradual decrease in the renal function spanning over a duration of several months to years without any major symptoms, is a life-threatening disease. It progresses in six stages according to the severit...
Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions.
JAMA network open
Aug 2, 2021
IMPORTANCE: Triage in the emergency department (ED) is a complex clinical judgment based on the tacit understanding of the patient's likelihood of survival, availability of medical resources, and local practices. Although a scoring tool could be valu...
Improving ED Emergency Severity Index Acuity Assignment Using Machine Learning and Clinical Natural Language Processing.
Journal of emergency nursing
Dec 24, 2020
INTRODUCTION: Triage is critical to mitigating the effect of increased volume by determining patient acuity, need for resources, and establishing acuity-based patient prioritization. The purpose of this retrospective study was to determine whether hi...
Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach.
Scientific reports
Dec 4, 2020
Mortality risk prediction can greatly improve the utilization of resources in intensive care units (ICUs). Existing schemes in ICUs today require laborious manual input of many complex parameters. In this work, we present a scheme that uses variation...
Machine learning and natural language processing methods to identify ischemic stroke, acuity and location from radiology reports.
PloS one
Jun 19, 2020
Accurate, automated extraction of clinical stroke information from unstructured text has several important applications. ICD-9/10 codes can misclassify ischemic stroke events and do not distinguish acuity or location. Expeditious, accurate data extra...
Early short-term prediction of emergency department length of stay using natural language processing for low-acuity outpatients.
The American journal of emergency medicine
Mar 10, 2020
BACKGROUND: Low-acuity outpatients constitute the majority of emergency department (ED) patients, and these patients often experience an unpredictable length of stay (LOS). Effective LOS prediction might improve the quality of ED care and reduce ED c...
A System for Automated Determination of Perioperative Patient Acuity.
Journal of medical systems
May 30, 2018
The widely used American Society of Anesthesiologists Physical Status (ASA PS) classification is subjective, requires manual clinician review to score, and has limited granularity. Our objective was to develop a system that automatically generates an...
Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: Results of unsupervised machine learning analysis.
Journal of evaluation in clinical practice
May 23, 2018
RATIONALE: Deficit schizophrenia, as defined by the Schedule for Deficit Syndrome, may represent a distinct diagnostic class defined by neurocognitive impairments coupled with changes in IgA/IgM responses to tryptophan catabolites (TRYCATs). Adequate...
Cytokines
Behavioral Symptoms
Patient Acuity
Female
Cognitive Reserve
Humans
Schizophrenia
Neurocognitive Disorders
Quality of Life
Adult
Psychotic Disorders
Neuroimmunomodulation
Male
Tryptophan
Middle Aged
Schizophrenic Psychology
Psychiatric Status Rating Scales
Inflammation
Unsupervised Machine Learning
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