AI Medical Compendium Topic:
Severity of Illness Index

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Application of Deep Learning in Quantitative Analysis of 2-Dimensional Ultrasound Imaging of Nonalcoholic Fatty Liver Disease.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine Jun 20, 2019
OBJECTIVES: To verify the value of deep learning in diagnosing nonalcoholic fatty liver disease (NAFLD) by comparing 3 image-processing techniques.
Sensitivity and Specificity Evaluation Studies as Topic Severity of Illness Index Non-alcoholic Fatty Liver Disease Deep Learning Image Interpretation, Computer-Assisted Ultrasonography Liver
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Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders.

IEEE journal of biomedical and health informatics Jun 17, 2019
Many classical machine learning techniques have been used to explore Alzheimer's disease (AD), evolving from image decomposition techniques such as principal component analysis toward higher complexity, non-linear decomposition algorithms. With the a...
Alzheimer Disease Mental Status and Dementia Tests Algorithms Databases, Factual Deep Learning Humans Brain Severity of Illness Index Cognitive Dysfunction Disease Progression Diagnosis, Computer-Assisted Magnetic Resonance Imaging
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Fully automatic knee osteoarthritis severity grading using deep neural networks with a novel ordinal loss.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jun 13, 2019
Knee osteoarthritis (OA) is one major cause of activity limitation and physical disability in older adults. Early detection and intervention can help slow down the OA degeneration. Physicians' grading based on visual inspection is subjective, varied ...
Neural Networks, Computer Severity of Illness Index Early Diagnosis Osteoarthritis, Knee Humans
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Computer-Aided Diagnosis and Clinical Trials of Cardiovascular Diseases Based on Artificial Intelligence Technologies for Risk-Early Warning Model.

Journal of medical systems Jun 13, 2019
The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical data. In order to achieve the regional medical and public health data analysis through ...
Prognosis Risk Assessment Severity of Illness Index Diagnosis, Computer-Assisted Bayes Theorem Logistic Models Humans Stroke Heart Failure Support Vector Machine Artificial Intelligence Data Mining Chronic Disease Renal Insufficiency Acute Disease
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An intelligent warning model for early prediction of cardiac arrest in sepsis patients.

Computer methods and programs in biomedicine Jun 11, 2019
BACKGROUND: Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early prediction of cardiac arrest can provide the time required for intervening and preventing its onset in order to reduce mortality. Several studies have be...
Decision Trees Monitoring, Ambulatory APACHE Multivariate Analysis Case-Control Studies Sepsis Adolescent Incidence Vital Signs Normal Distribution Heart Arrest Female Reproducibility of Results Young Adult Adult Sensitivity and Specificity Male Middle Aged Severity of Illness Index Humans Machine Learning Algorithms Electronic Health Records
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Long-Dose Intensive Therapy Is Necessary for Strong, Clinically Significant, Upper Limb Functional Gains and Retained Gains in Severe/Moderate Chronic Stroke.

Neurorehabilitation and neural repair May 25, 2019
. Effective treatment methods are needed for moderate/severely impairment chronic stroke. . The questions were the following: (1) Is there need for long-dose therapy or is there a mid-treatment plateau? (2) Are the observed gains from the prior-studi...
Recovery of Function Outcome and Process Assessment, Health Care Chronic Disease Adult Robotics Stroke Humans Male Single-Blind Method Female Motor Skills Middle Aged Aged Upper Extremity Severity of Illness Index Young Adult Stroke Rehabilitation
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Classifying intracranial stenosis disease severity from functional MRI data using machine learning.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism May 8, 2019
Translation of many non-invasive hemodynamic MRI methods to cerebrovascular disease patients has been hampered by well-known artifacts associated with delayed blood arrival times and reduced microvascular compliance. Using machine learning and suppor...
Humans Machine Learning Brain Sensitivity and Specificity Middle Aged Severity of Illness Index Female Moyamoya Disease Young Adult Case-Control Studies Cerebral Angiography Image Processing, Computer-Assisted Magnetic Resonance Angiography Cerebrovascular Circulation
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Performance of a Deep Learning Model vs Human Reviewers in Grading Endoscopic Disease Severity of Patients With Ulcerative Colitis.

JAMA network open May 3, 2019
IMPORTANCE: Assessing endoscopic disease severity in ulcerative colitis (UC) is a key element in determining therapeutic response, but its use in clinical practice is limited by the requirement for experienced human reviewers.
Reproducibility of Results Video Recording Humans Colonoscopy Adult Retrospective Studies Male Severity of Illness Index Female Middle Aged Deep Learning Colitis, Ulcerative
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Development and Validation of Machine Learning Models in Prediction of Remission in Patients With Moderate to Severe Crohn Disease.

JAMA network open May 3, 2019
IMPORTANCE: Biological therapies have revolutionized inflammatory bowel disease management, but many patients do not respond to biological monotherapy. Identification of likely responders could reduce costs and delays in remission.
Ustekinumab Humans Machine Learning Female Adult C-Reactive Protein Crohn Disease Remission Induction Biological Therapy Male Middle Aged Severity of Illness Index Predictive Value of Tests
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Deep learning to automate Brasfield chest radiographic scoring for cystic fibrosis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society May 2, 2019
BACKGROUND: The aim of this study was to evaluate the hypothesis that a deep convolutional neural network (DCNN) model could facilitate automated Brasfield scoring of chest radiographs (CXRs) for patients with cystic fibrosis (CF), performing similar...
Child Cystic Fibrosis Research Design Pediatrics Prognosis Radiography, Thoracic Tomography, X-Ray Computed Humans Lung Female Reproducibility of Results Neural Networks, Computer Severity of Illness Index Male Deep Learning
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