AIMC Topic: Severity of Illness Index

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Development and validation of three machine-learning models for predicting multiple organ failure in moderately severe and severe acute pancreatitis.

BMC gastroenterology Jul 4, 2019
BACKGROUND: Multiple organ failure (MOF) is a serious complication of moderately severe (MASP) and severe acute pancreatitis (SAP). This study aimed to develop and assess three machine-learning models to predict MOF.
Machine Learning Prognosis Retrospective Studies Female Adult Humans Multiple Organ Failure Predictive Value of Tests Acute Disease APACHE Pancreatitis Male Middle Aged Risk Assessment Severity of Illness Index Logistic Models
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Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy Using Quantitative Proteomics and Machine Learning.

Molecular & cellular proteomics : MCP Jun 26, 2019
Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It is the commonest inherited cardiac condition and a significant number of high risk cases still go undetected until a sudden cardiac death (SCD) event....
Humans Female Middle Aged Aged Young Adult Peptides Predictive Value of Tests Machine Learning Severity of Illness Index Mutation Adult Phenotype Case-Control Studies Male Cardiomyopathy, Hypertrophic Proteomics Prospective Studies Hypertrophy, Left Ventricular Biomarkers Sarcomeres
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Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning.

Radiology Jun 25, 2019
Background Coronary CT angiography contains prognostic information but the best method to extract these data remains unknown. Purpose To use machine learning to develop a model of vessel features to discriminate between patients with and without subs...
Computed Tomography Angiography Coronary Angiography Coronary Artery Disease Image Interpretation, Computer-Assisted Coronary Vessels Risk Factors Aged Aged, 80 and over Young Adult Adult Male Middle Aged Severity of Illness Index Predictive Value of Tests Humans Machine Learning Female Reproducibility of Results
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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 Severity of Illness Index Deep Learning Ultrasonography Liver Evaluation Studies as Topic Non-alcoholic Fatty Liver Disease Image Interpretation, Computer-Assisted
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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...
Algorithms Databases, Factual Brain Disease Progression Severity of Illness Index Humans Alzheimer Disease Mental Status and Dementia Tests Diagnosis, Computer-Assisted Deep Learning Cognitive Dysfunction 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 ...
Osteoarthritis, Knee Humans Neural Networks, Computer Severity of Illness Index Early Diagnosis
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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 ...
Risk Assessment Heart Failure Data Mining Severity of Illness Index Renal Insufficiency Diagnosis, Computer-Assisted Logistic Models Humans Support Vector Machine Artificial Intelligence Chronic Disease Prognosis Acute Disease Bayes Theorem Stroke
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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...
Incidence Decision Trees Monitoring, Ambulatory APACHE Multivariate Analysis Machine Learning Vital Signs Normal Distribution Algorithms Heart Arrest Electronic Health Records Middle Aged Female Severity of Illness Index Reproducibility of Results Humans Case-Control Studies Young Adult Sepsis Adult Adolescent Sensitivity and Specificity Male
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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...
Chronic Disease Adult Motor Skills Robotics Male Humans Single-Blind Method Middle Aged Upper Extremity Stroke Female Severity of Illness Index Stroke Rehabilitation Aged Recovery of Function Outcome and Process Assessment, Health Care Young Adult
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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...
Sensitivity and Specificity Middle Aged Severity of Illness Index Humans Case-Control Studies Machine Learning Magnetic Resonance Angiography Image Processing, Computer-Assisted Brain Cerebrovascular Circulation Female Moyamoya Disease Young Adult Cerebral Angiography
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