AIMC Topic: Logistic Models

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Comparing Logistic Regression Models with Alternative Machine Learning Methods to Predict the Risk of Drug Intoxication Mortality.

International journal of environmental research and public health Jan 31, 2020
(1) Medical research has shown an increasing interest in machine learning, permitting massive multivariate data analysis. Thus, we developed drug intoxication mortality prediction models, and compared machine learning models and traditional logistic ...
Republic of Korea Risk Assessment Logistic Models Area Under Curve Mortality Alcoholic Intoxication Neural Networks, Computer Machine Learning
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Mixed-integer optimization approach to learning association rules for unplanned ICU transfer.

Artificial intelligence in medicine Jan 30, 2020
After admission to emergency department (ED), patients with critical illnesses are transferred to intensive care unit (ICU) due to unexpected clinical deterioration occurrence. Identifying such unplanned ICU transfers is urgently needed for medical p...
Patient Transfer Hospitals, Teaching Age Factors Emergency Service, Hospital Quality Improvement Severity of Illness Index Time Factors Logistic Models Models, Theoretical Humans Machine Learning Critical Illness Intensive Care Units
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Acceptability of artificial intelligence (AI)-enabled chatbots, video consultations and live webchats as online platforms for sexual health advice.

BMJ sexual & reproductive health Jan 21, 2020
OBJECTIVES: Sexual and reproductive health (SRH) services are undergoing a digital transformation. This study explored the acceptability of three digital services, (i) video consultations via Skype, (ii) live webchats with a health advisor and (iii) ...
Humans Artificial Intelligence Logistic Models Internet United Kingdom Patient Acceptance of Health Care Sexual Health Hotlines Reproductive Health Services Male Middle Aged Surveys and Questionnaires Female Adolescent Aged Adult Cross-Sectional Studies
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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...
Liver Equipment Design Electrophysiology Phantoms, Imaging Electrophysiological Phenomena Logistic Models Rats, Wistar Rats Liver Cirrhosis Algorithms Female Animals Machine Learning
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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...
Cohort Studies Logistic Models Bariatric Surgery Venous Thromboembolism Databases, Factual Adult Postoperative Complications Diagnosis, Computer-Assisted Anastomotic Leak Humans Neural Networks, Computer Machine Learning
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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 ROC Curve Logistic Models Menisci, Tibial Tibial Meniscus Injuries Female Male 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...
Female Aged Young Adult Adult Humans Machine Learning Electronic Health Records Logistic Models Atrial Fibrillation Male Middle Aged Risk Assessment
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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.
Electronic Health Records Female Outcome Assessment, Health Care Hospitalization Humans Aged, 80 and over Logistic Models Aged United States Machine Learning Male Medicare Comorbidity Heart Failure 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 Algorithms Gene Expression
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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...
Radiography Tomography, X-Ray Computed Emergency Service, Hospital Adolescent Child, Preschool Child Logistic Models United States Socioeconomic Factors Triage Natural Language Processing Health Care Surveys Patient Acceptance of Health Care Humans Female Male Infant
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