AI Medical Compendium Topic:
Logistic Models

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Multiclass Classification of Hepatic Anomalies with Dielectric Properties: From Phantom Materials to Rat Hepatic Tissues.

Sensors (Basel, Switzerland) Jan 18, 2020
Open-ended coaxial probes can be used as tissue characterization devices. However, the technique suffers from a high error rate. To improve this technology, there is a need to decrease the measurement error which is reported to be more than 30% for a...
Electrophysiology Phantoms, Imaging Electrophysiological Phenomena Liver Cirrhosis Liver Equipment Design Machine Learning Algorithms Female Rats, Wistar Animals Rats Logistic Models
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Development and validation of machine learning models to predict gastrointestinal leak and venous thromboembolism after weight loss surgery: an analysis of the MBSAQIP database.

Surgical endoscopy Jan 17, 2020
BACKGROUND: Postoperative gastrointestinal leak and venous thromboembolism (VTE) are devastating complications of bariatric surgery. The performance of currently available predictive models for these complications remains wanting, while machine learn...
Anastomotic Leak Logistic Models Bariatric Surgery Venous Thromboembolism Neural Networks, Computer Humans Diagnosis, Computer-Assisted Cohort Studies Adult Postoperative Complications Machine Learning Databases, Factual
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Predictive validity of radiographic signs of complete discoid lateral meniscus in children using machine learning techniques.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society Jan 3, 2020
The diagnostic utility of radiographic signs of complete discoid lateral meniscus remains controversial. This study aimed to investigate the diagnostic accuracy and determine which sign is most reliably detects the presence of a complete discoid late...
Humans Machine Learning Retrospective Studies Female ROC Curve Logistic Models Menisci, Tibial Male Tibial Meniscus Injuries Adolescent Child
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Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation.

JAMA network open Jan 3, 2020
IMPORTANCE: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its early detection could lead to significant improvements in outcomes through the appropriate prescription of anticoagulation medication. Although a variety of...
Humans Machine Learning Electronic Health Records Adult Male Middle Aged Risk Assessment Female Aged Young Adult Logistic Models Atrial Fibrillation
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Comparison of Machine Learning Methods With Traditional Models for Use of Administrative Claims With Electronic Medical Records to Predict Heart Failure Outcomes.

JAMA network open Jan 3, 2020
IMPORTANCE: Accurate risk stratification of patients with heart failure (HF) is critical to deploy targeted interventions aimed at improving patients' quality of life and outcomes.
Medicare Heart Failure Outcome Assessment, Health Care Aged Aged, 80 and over Machine Learning Male Electronic Health Records Logistic Models Female Humans Comorbidity United States Hospitalization Cohort Studies
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Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research.

Journal of biomedical informatics Dec 31, 2019
OBJECTIVE: The speed of the diagnosis process is vital in pursuing the trial of curing cancer. During the last decade, precision medicine evolved by detecting different types of cancer through microarrays (MA) of deoxyribonucleic acid (DNA) processed...
Neoplasms Neural Networks, Computer Logistic Models Machine Learning Gene Expression Algorithms
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Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department.

BMC medical informatics and decision making Dec 30, 2019
OBJECTIVE: To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clinical factors during the patients' ED visits; and to develop predictive models using these associated...
Socioeconomic Factors Triage Humans Emergency Service, Hospital Child Natural Language Processing Adolescent Tomography, X-Ray Computed Health Care Surveys Logistic Models Male Radiography Child, Preschool Female Patient Acceptance of Health Care United States Infant
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Comparing context-dependent call sequences employing machine learning methods: an indication of syntactic structure of greater horseshoe bats.

The Journal of experimental biology Dec 18, 2019
For analysis of vocal syntax, accurate classification of call sequence structures in different behavioural contexts is essential. However, an effective, intelligent program for classifying call sequences from numerous recorded sound files is still la...
Machine Learning Decision Trees Animals Chiroptera Vocalization, Animal Logistic Models Echolocation Support Vector Machine
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Highway crash detection and risk estimation using deep learning.

Accident; analysis and prevention Dec 13, 2019
Crash Detection is essential in providing timely information to traffic management centers and the public to reduce its adverse effects. Prediction of crash risk is vital for avoiding secondary crashes and safeguarding highway traffic. For many years...
Accidents, Traffic Data Collection Humans Deep Learning Risk Assessment Logistic Models
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Classification of Depression Patients and Normal Subjects Based on Electroencephalogram (EEG) Signal Using Alpha Power and Theta Asymmetry.

Journal of medical systems Dec 13, 2019
Depression or Major Depressive Disorder (MDD) is a mental illness which negatively affects how a person thinks, acts or feels. MDD has become a major disease affecting millions of people presently. The diagnosis of depression is questionnaire based a...
Depressive Disorder, Major Image Processing, Computer-Assisted Logistic Models Electroencephalography Support Vector Machine Bayes Theorem Female Adult Male Middle Aged Humans
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