AIMC Topic: Severity of Illness Index

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Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.

Critical care (London, England) Feb 6, 2020
BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing co...
Area Under Curve APACHE Organ Dysfunction Scores Mortality Male Middle Aged Severity of Illness Index ROC Curve Humans Machine Learning Republic of Korea Algorithms Continuous Renal Replacement Therapy Acute Kidney Injury Female Risk Factors Aged Aged, 80 and over
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Development and Validation of a Multitask Deep Learning Model for Severity Grading of Hip Osteoarthritis Features on Radiographs.

Radiology Feb 4, 2020
Background A multitask deep learning model might be useful in large epidemiologic studies wherein detailed structural assessment of osteoarthritis still relies on expert radiologists' readings. The potential of such a model in clinical routine should...
Humans Severity of Illness Index Deep Learning Models, Theoretical Radiography Osteoarthritis, Hip Retrospective Studies Female Aged Male Middle Aged
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Mixed-integer optimization approach to learning association rules for unplanned ICU transfer.

Artificial intelligence in medicine Jan 30, 2020
After admission to emergency department (ED), patients with critical illnesses are transferred to intensive care unit (ICU) due to unexpected clinical deterioration occurrence. Identifying such unplanned ICU transfers is urgently needed for medical p...
Age Factors Emergency Service, Hospital Quality Improvement Patient Transfer Hospitals, Teaching Severity of Illness Index Time Factors Logistic Models Models, Theoretical Humans Machine Learning Critical Illness Intensive Care Units
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Automated classification of normal and Stargardt disease optical coherence tomography images using deep learning.

Acta ophthalmologica Jan 24, 2020
PURPOSE: Recent advances in deep learning have seen an increase in its application to automated image analysis in ophthalmology for conditions with a high prevalence. We wanted to identify whether deep learning could be used for the automated classif...
Adult Male Middle Aged Severity of Illness Index Deep Learning Humans Case-Control Studies ROC Curve Female Image Processing, Computer-Assisted Tomography, Optical Coherence Stargardt Disease
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Observer-independent assessment of psoriasis-affected area using machine learning.

Journal of the European Academy of Dermatology and Venereology : JEADV Jan 23, 2020
BACKGROUND: Assessment of psoriasis severity is strongly observer-dependent, and objective assessment tools are largely missing. The increasing number of patients receiving highly expensive therapies that are reimbursed only for moderate-to-severe ps...
Machine Learning Retrospective Studies Reproducibility of Results Aged Aged, 80 and over Humans Neural Networks, Computer Adolescent Psoriasis Observer Variation Photography Young Adult Adult Middle Aged Severity of Illness Index
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The Role of Robotic Path Assistance and Weight Support in Facilitating 3D Movements in Individuals With Poststroke Hemiparesis.

Neurorehabilitation and neural repair Jan 20, 2020
. High-intensity repetitive training is challenging to provide poststroke. Robotic approaches can facilitate such training by unweighting the limb and/or by improving trajectory control, but the extent to which these types of assistance are necessary...
Stroke Psychomotor Performance Paresis Exoskeleton Device Motor Activity Upper Extremity Stroke Rehabilitation Outcome and Process Assessment, Health Care Humans Biomechanical Phenomena Female Male Aged Middle Aged Adult Severity of Illness Index Robotics
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Assessing stroke severity using electronic health record data: a machine learning approach.

BMC medical informatics and decision making Jan 8, 2020
BACKGROUND: Stroke severity is an important predictor of patient outcomes and is commonly measured with the National Institutes of Health Stroke Scale (NIHSS) scores. Because these scores are often recorded as free text in physician reports, structur...
Aged Aged, 80 and over Male Middle Aged Severity of Illness Index Machine Learning Databases, Factual Electronic Health Records Female Cohort Studies Natural Language Processing Stroke Humans
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Gait characteristics and clinical relevance of hereditary spinocerebellar ataxia on deep learning.

Artificial intelligence in medicine Jan 7, 2020
BACKGROUND: Deep learning has always been at the forefront of scientific research. It has also been applied to medical research. Hereditary spinocerebellar ataxia (SCA) is characterized by gait abnormalities and is usually evaluated semi-quantitative...
Humans Female Aged Young Adult Adult Biomechanical Phenomena Male Middle Aged Severity of Illness Index Gait Deep Learning Sex Factors Age Factors Spinocerebellar Ataxias Magnetic Resonance Imaging Single-Blind Method
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A modern approach to identifying and characterizing child asthma and wheeze phenotypes based on clinical data.

PloS one Dec 30, 2019
'Asthma' is a complex disease that encapsulates a heterogeneous group of phenotypes and endotypes. Research to understand these phenotypes has previously been based on longitudinal wheeze patterns or hypothesis-driven observational criteria. The aim ...
Severity of Illness Index Diseases in Twins Adolescent Female Humans Eosinophils Child Sweden Machine Learning Medical History Taking Regression Analysis Risk Factors Data Analysis Leukocyte Count Asthma Biomarkers Respiratory Sounds Male Twins
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Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA.

Atherosclerosis Dec 23, 2019
BACKGROUND AND AIMS: Artificial intelligence (AI) is increasing its role in diagnosis of patients with suspicious coronary artery disease. The aim of this manuscript is to develop a deep convolutional neural network (CNN) to classify coronary compute...
Female Aged Male Middle Aged Severity of Illness Index Computed Tomography Angiography Deep Learning Humans Predictive Value of Tests Algorithms Coronary Angiography Retrospective Studies Coronary Artery Disease
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