AIMC Topic: Logistic Models

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Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma.

BMC medical informatics and decision making Nov 8, 2019
BACKGROUND: Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. Recently, deep learning models have achieved state-of-the-a...
Humans Algorithms Prognosis Child, Preschool Child Logistic Models Predictive Value of Tests Electronic Health Records Clinical Decision-Making Asthma Risk Assessment Deep Learning
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Using machine learning to predict opioid misuse among U.S. adolescents.

Preventive medicine Nov 6, 2019
This study evaluated prediction performance of three different machine learning (ML) techniques in predicting opioid misuse among U.S. adolescents. Data were drawn from the 2015-2017 National Survey on Drug Use and Health (N = 41,579 adolescents, age...
Area Under Curve Opioid-Related Disorders Child Logistic Models United States Adolescent Behavior Humans Machine Learning Algorithms Female Male Risk Assessment Surveys and Questionnaires Adolescent
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Clear cell renal cell carcinoma: Machine learning-based computed tomography radiomics analysis for the prediction of WHO/ISUP grade.

European journal of radiology Nov 6, 2019
PURPOSE: To evaluate the performance of machine learning (ML)-based computed tomography (CT) radiomics analysis for discriminating between low grade (WHO/ISUP I-II) and high grade (WHO/ISUP III-IV) clear cell renal cell carcinomas (ccRCCs).
Kidney Neoplasms Carcinoma, Renal Cell Support Vector Machine Machine Learning Diagnosis, Differential Humans Algorithms Male Predictive Value of Tests Retrospective Studies Reproducibility of Results Middle Aged Neoplasm Grading Tomography, X-Ray Computed Aged Image Interpretation, Computer-Assisted Kidney Female Aged, 80 and over Logistic Models Young Adult Adult
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A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.

BMC medical informatics and decision making Nov 6, 2019
BACKGROUND: Diabetes and cardiovascular disease are two of the main causes of death in the United States. Identifying and predicting these diseases in patients is the first step towards stopping their progression. We evaluate the capabilities of mach...
Humans Support Vector Machine Predictive Value of Tests Machine Learning Cardiovascular Diseases Electronic Health Records ROC Curve Female Logistic Models Male Nutrition Surveys Diabetes Mellitus
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A machine-learning approach to predict postprandial hypoglycemia.

BMC medical informatics and decision making Nov 6, 2019
BACKGROUND: For an effective artificial pancreas (AP) system and an improved therapeutic intervention with continuous glucose monitoring (CGM), predicting the occurrence of hypoglycemia accurately is very important. While there have been many studies...
Hypoglycemic Agents Support Vector Machine Hypoglycemia Blood Glucose Self-Monitoring Retrospective Studies Humans Adult Machine Learning Sensitivity and Specificity Algorithms Blood Glucose Logistic Models
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Predicting skilled delivery service use in Ethiopia: dual application of logistic regression and machine learning algorithms.

BMC medical informatics and decision making Nov 5, 2019
BACKGROUND: Skilled assistance during childbirth is essential to reduce maternal deaths. However, in Ethiopia, which is among the six countries contributing to more than half of the global maternal deaths, the coverage of births attended by skilled h...
Machine Learning Clinical Decision-Making Pregnancy Female Young Adult Humans Health Surveys Logistic Models Ethiopia Bayes Theorem Delivery, Obstetric Adult Cross-Sectional Studies Middle Aged Maternal Health Services Adolescent
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Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning.

Nature communications Oct 30, 2019
Raman optical spectroscopy promises label-free bacterial detection, identification, and antibiotic susceptibility testing in a single step. However, achieving clinically relevant speeds and accuracies remains challenging due to weak Raman signal from...
Enterococcus Streptococcus Support Vector Machine Bacterial Typing Techniques Microbial Sensitivity Tests Humans Proteus mirabilis Escherichia coli Bacterial Infections Single-Cell Analysis Neural Networks, Computer Principal Component Analysis Staphylococcus aureus Bacteria Anti-Bacterial Agents Pseudomonas aeruginosa Methicillin-Resistant Staphylococcus aureus Logistic Models Deep Learning Salmonella enterica Candida Spectrum Analysis, Raman Klebsiella
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A question-entailment approach to question answering.

BMC bioinformatics Oct 22, 2019
BACKGROUND: One of the challenges in large-scale information retrieval (IR) is developing fine-grained and domain-specific methods to answer natural language questions. Despite the availability of numerous sources and datasets for answer retrieval, Q...
Deep Learning Logistic Models Information Storage and Retrieval Medical Informatics Unified Medical Language System
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Depression Prediction by Using Ecological Momentary Assessment, Actiwatch Data, and Machine Learning: Observational Study on Older Adults Living Alone.

JMIR mHealth and uHealth Oct 16, 2019
BACKGROUND: Although geriatric depression is prevalent, diagnosis using self-reporting instruments has limitations when measuring the depressed mood of older adults in a community setting. Ecological momentary assessment (EMA) by using wearable devic...
Logistic Models Residence Characteristics Ecological Momentary Assessment Aged, 80 and over Male Humans Depression Machine Learning Surveys and Questionnaires Republic of Korea Wearable Electronic Devices Female Aged
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Atrial Fibrillation Burden Signature and Near-Term Prediction of Stroke: A Machine Learning Analysis.

Circulation. Cardiovascular quality and outcomes Oct 15, 2019
BACKGROUND: Atrial fibrillation (AF) increases the risk of stroke 5-fold and there is rising interest to determine if AF severity or burden can further risk stratify these patients, particularly for near-term events. Using continuous remote monitorin...
Female Risk Factors Aged Aged, 80 and over Male Middle Aged Risk Assessment Diagnosis, Computer-Assisted Time Factors Logistic Models Neural Networks, Computer Machine Learning Prognosis Retrospective Studies Electronic Health Records Proof of Concept Study Administrative Claims, Healthcare Humans Telemetry United States Veterans Health Services Predictive Value of Tests Signal Processing, Computer-Assisted Stroke Atrial Fibrillation
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