AIMC Topic: Predictive Value of Tests
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To Generate an Ensemble Model for Women Thyroid Prediction Using Data Mining Techniques.
Asian Pacific journal of cancer prevention : APJCP
Apr 29, 2019
Objective: The main objective of this paper is to easily identify thyroid symptom for treatment. Methods: In this paper two main techniques are proposed for mining the hidden pattern in the dataset. Ensemble-I and Ensemble- II both are machine learni...
Advanced atherosclerosis imaging by CT: Radiomics, machine learning and deep learning.
Journal of cardiovascular computed tomography
Apr 21, 2019
In the last decade, technical advances in the field of medical imaging significantly improved and broadened the application of coronary CT angiography (CCTA) for the non-invasive assessment of coronary artery disease. Recently, similar breakthroughs ...
New Multiparametric Analysis of Cardiac Dyssynchrony: Machine Learning and Prediction of Response to CRT.
JACC. Cardiovascular imaging
Apr 17, 2019
Echocardiography
Electrocardiography
Treatment Outcome
Decision Support Techniques
Cardiac Resynchronization Therapy
Predictive Value of Tests
Signal Processing, Computer-Assisted
Ventricular Dysfunction, Left
Humans
Retrospective Studies
Heart Failure
Image Interpretation, Computer-Assisted
Clinical Decision-Making
Machine Learning
Ventricular Function, Left
Machine learning algorithms for the detection of spurious white blood cell differentials due to erythrocyte lysis resistance.
Journal of clinical pathology
Apr 16, 2019
AIMS: Red blood cell (RBC) lysis resistance interferes with white blood cell (WBC) count and differential; still, its detection relies on the identification of an abnormal scattergram, and this is not clearly adverted by specific flags in the Beckman...
Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia.
International journal of geriatric psychiatry
Apr 15, 2019
OBJECTIVES: The overall aim of the present study was to explore the role of cognitive reserve (CR) in the conversion from mild cognitive impairment (MCI) to dementia. We used traditional and machine learning (ML) techniques to compare converter and n...
Machine Learning Readmission Risk Modeling: A Pediatric Case Study.
BioMed research international
Apr 15, 2019
BACKGROUND: Hospital readmission prediction in pediatric hospitals has received little attention. Studies have focused on the readmission frequency analysis stratified by disease and demographic/geographic characteristics but there are no predictive ...
Dense networks with relative location awareness for thorax disease identification.
Medical physics
Apr 14, 2019
PURPOSE: Chest X-ray is one of the most common examinations for diagnosing heart and lung diseases. Due to the existing of a large number of clinical cases, many automated diagnosis algorithms based on chest X-ray images have been proposed. To our kn...
Predicting daily outcomes in acetaminophen-induced acute liver failure patients with machine learning techniques.
Computer methods and programs in biomedicine
Apr 11, 2019
BACKGROUND/OBJECTIVE: Assessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF) patients during the first week of hospitalization often presents significant challenges. Current models such as the King's College Criteria (KCC) and t...
Middle Aged
Severity of Illness Index
ROC Curve
Databases, Factual
Humans
Linear Models
Treatment Outcome
Prognosis
Machine Learning
Female
Predictive Value of Tests
Acetaminophen
Liver Failure, Acute
Retrospective Studies
Adult
Area Under Curve
Sensitivity and Specificity
Bayes Theorem
Male
Registries
Identifying Factors That Affect Patient Survival After Orthotopic Liver Transplant Using Machine-Learning Techniques.
Experimental and clinical transplantation : official journal of the Middle East Society for Organ Transplantation
Apr 9, 2019
OBJECTIVES: Survival after liver transplant depends on pretransplant, peritransplant, and posttransplant factors. Identifying effective factors for patient survival after transplant can help transplant centers make better decisions.
Evidential MACE prediction of acute coronary syndrome using electronic health records.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Major adverse cardiac event (MACE) prediction plays a key role in providing efficient and effective treatment strategies for patients with acute coronary syndrome (ACS) during their hospitalizations. Existing prediction models have limita...
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