AIMC Topic: Severity of Illness Index

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Objective evaluation of allergic conjunctival disease (with a focus on the application of artificial intelligence technology).

Allergology international : official journal of the Japanese Society of Allergology Jun 17, 2020
We have summarized the past efforts and results of objective measurement methods for conjunctival hyperemia classification. Severity classification using conjunctival blood vessel occupancy rate, ocular surface temperature analysis, and artificial in...
Artificial Intelligence Severity of Illness Index Hyperemia Slit Lamp Microscopy Conjunctivitis, Allergic Humans
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Defining heterogeneity of epicardial functional stenosis with low coronary flow reserve by unsupervised machine learning.

Heart and vessels Jun 6, 2020
Low CFR is associated with poor prognosis, whereas it is a heterogeneous condition according to the actual coronary flow, such as high resting or low hyperemic coronary flow, which should have different physiological traits and clinical implications....
Humans Prognosis Republic of Korea Female Aged Unsupervised Machine Learning Predictive Value of Tests Registries Japan Spain Male Middle Aged Severity of Illness Index Diagnosis, Computer-Assisted Cluster Analysis Blood Flow Velocity Cardiac Catheterization Coronary Stenosis Fractional Flow Reserve, Myocardial Hyperemia
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Applying cascaded convolutional neural network design further enhances automatic scoring of arthritis disease activity on ultrasound images from rheumatoid arthritis patients.

Annals of the rheumatic diseases Jun 5, 2020
OBJECTIVES: We have previously shown that neural network technology can be used for scoring arthritis disease activity in ultrasound images from rheumatoid arthritis (RA) patients, giving scores according to the EULAR-OMERACT grading system. We have ...
Male Middle Aged Severity of Illness Index Humans Ultrasonography Arthritis, Rheumatoid Neural Networks, Computer Image Interpretation, Computer-Assisted Female Clinical Trials as Topic Reproducibility of Results Joints Adult Rheumatology Synovitis
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Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients.

PloS one Jun 5, 2020
Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optimal time, either with hemodialysis or kidney transplantation, is crucial for patient's well-being and for successful management of the condition. In thi...
Renal Insufficiency, Chronic Taiwan Models, Biological Datasets as Topic Humans Time-to-Treatment Machine Learning Disease Progression Retrospective Studies Comorbidity Renal Replacement Therapy Severity of Illness Index Clinical Decision-Making Time Factors ROC Curve
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An innovative method for screening and evaluating the degree of diabetic retinopathy and drug treatment based on artificial intelligence algorithms.

Pharmacological research Jun 2, 2020
Current methods of evaluating the degree of diabetic retinopathy are highly subjective and have no quantitative standard. To objectively evaluate the slight changes in tissue structure during the early stage of retinal diseases, a subjective interpre...
Diabetes Mellitus, Type 2 Mice Rats, Wistar Diabetes Mellitus, Type 1 Hypoglycemic Agents Diabetic Retinopathy Animals Male Image Interpretation, Computer-Assisted Severity of Illness Index Early Diagnosis Deep Learning Predictive Value of Tests Retinal Ganglion Cells Drugs, Chinese Herbal Pattern Recognition, Automated Diabetes Mellitus, Experimental Retinal Vessels Retina Microscopy
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A Comparative Study of the Diagnostic Potential of Plasma and Erythrocytic α-Synuclein in Parkinson's Disease.

Neuro-degenerative diseases Jun 2, 2020
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disease characterized by intracellular α-synuclein (α-Syn) deposition. Alternation of the α-Syn expression level in plasma or erythrocytes may be used as a potential PD biomarker. However, n...
Aged, 80 and over Severity of Illness Index Humans Adult Enzyme-Linked Immunosorbent Assay Biomarkers Sensitivity and Specificity Parkinson Disease Female Male alpha-Synuclein Aged Middle Aged Erythrocytes
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Predicting individual improvement in schizophrenia symptom severity at 1-year follow-up: Comparison of connectomic, structural, and clinical predictors.

Human brain mapping May 29, 2020
In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at bas...
Young Adult Adult Sensitivity and Specificity Male Severity of Illness Index Follow-Up Studies Magnetic Resonance Imaging Schizophrenia Antipsychotic Agents Neuroimaging Humans Machine Learning Prognosis Gray Matter Female Cerebral Cortex Connectome Default Mode Network
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Impact of machine learning-based coronary computed tomography angiography fractional flow reserve on treatment decisions and clinical outcomes in patients with suspected coronary artery disease.

European radiology May 28, 2020
OBJECTIVES: This study investigated the impact of machine learning (ML)-based fractional flow reserve derived from computed tomography (FFR) compared to invasive coronary angiography (ICA) for therapeutic decision-making and patient outcome in patien...
Fractional Flow Reserve, Myocardial Coronary Angiography Coronary Artery Disease Disease Management Computed Tomography Angiography Male Middle Aged Severity of Illness Index Humans Decision Making Artificial Intelligence Predictive Value of Tests Machine Learning Retrospective Studies Female
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Detection of Depression and Scaling of Severity Using Six Channel EEG Data.

Journal of medical systems May 21, 2020
Depression is a psychiatric problem which affects the growth of a person, like how a person thinks, feels and behaves. The major reason behind wrong diagnosis of depression is absence of any laboratory test for detection as well as severity scaling o...
Severity of Illness Index Algorithms Support Vector Machine Brain Electroencephalography Humans Female Signal Processing, Computer-Assisted Adult Depressive Disorder Male
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Unsupervised Cluster Analysis of Patients With Aortic Stenosis Reveals Distinct Population With Different Phenotypes and Outcomes.

Circulation. Cardiovascular imaging May 18, 2020
BACKGROUND: There is a lack of studies investigating the heterogeneity of patients with aortic stenosis (AS). We explored whether cluster analysis identifies distinct subgroups with different prognostic significances in AS.
Severity of Illness Index Hemodynamics Age Factors Cluster Analysis Aortic Valve Stenosis Aortic Valve Unsupervised Machine Learning Humans Predictive Value of Tests Decision Support Techniques Cause of Death Aged, 80 and over Phenotype Female Male Prospective Studies Reproducibility of Results Echocardiography Prognosis Risk Factors Middle Aged Aged Comorbidity
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