AIMC Topic: Logistic Models

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[Application of recurrent neural network in prognosis of peritoneal dialysis].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences Jun 18, 2019
OBJECTIVE: Deep learning models, including recurrent neural network (RNN) and gated recurrent unit (GRU), were used to construct the clinical prognostic prediction models for peritoneal dialysis (PD) patients based on routine clinical data. The perfo...
Prognosis Logistic Models Databases, Genetic Peritoneal Dialysis Humans Neural Networks, Computer
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Exploring the survival prognosis of lung adenocarcinoma based on the cancer genome atlas database using artificial neural network.

Medicine May 1, 2019
The aim of this study was to investigate the clinical factors affecting the survival prognosis of lung adenocarcinoma, and to establish a predictive model of survival prognosis of lung adenocarcinoma by artificial neural network.Download the cancer g...
Predictive Value of Tests Neoplasm Staging Cigarette Smoking Kaplan-Meier Estimate ROC Curve Lung Neoplasms Logistic Models Regression Analysis Adenocarcinoma of Lung Genomic Library Humans Aged, 80 and over Neural Networks, Computer Adult Male Middle Aged Prognosis Female Risk Factors Aged
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Machine Learning for the Prediction of New-Onset Diabetes Mellitus during 5-Year Follow-up in Non-Diabetic Patients with Cardiovascular Risks.

Yonsei medical journal Feb 1, 2019
PURPOSE: Many studies have proposed predictive models for type 2 diabetes mellitus (T2DM). However, these predictive models have several limitations, such as user convenience and reproducibility. The purpose of this study was to develop a T2DM predic...
Humans Reproducibility of Results Risk Factors Male Cardiovascular Diseases Machine Learning Algorithms Republic of Korea Female Logistic Models Follow-Up Studies Middle Aged ROC Curve Diabetes Mellitus, Type 2
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Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning.

Chemical communications (Cambridge, England) Jan 10, 2019
Combined single cell mass spectrometry and machine learning methods is demonstrated for the first time to achieve rapid and reliable prediction of the phenotype of unknown single cells based on their metabolomic profiles, with experimental validation...
K562 Cells Stochastic Processes Leukemia, Myelogenous, Chronic, BCR-ABL Positive Logistic Models Mass Spectrometry Metabolomics Drug Resistance, Neoplasm Machine Learning Phenotype Single-Cell Analysis Humans Neural Networks, Computer
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A Machine Learning Recommender System to Tailor Preference Assessments to Enhance Person-Centered Care Among Nursing Home Residents.

The Gerontologist Jan 9, 2019
BACKGROUND AND OBJECTIVES: Nursing homes (NHs) using the Preferences for Everyday Living Inventory (PELI-NH) to assess important preferences and provide person-centered care find the number of items (72) to be a barrier to using the assessment.
Nursing Homes Patient Preference Long-Term Care United States Patient-Centered Care Quality of Health Care Humans Machine Learning Qualitative Research Interviews as Topic Logistic Models
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Hematological disturbances in Down syndrome: single centre experience of thirteen years and review of the literature.

The Turkish journal of pediatrics Jan 1, 2019
Karakurt N, Uslu İ, Aygün C, Albayrak C. Hematological disturbances in Down syndrome: single centre experience of thirteen years and review of the literature. Turk J Pediatr 2019; 61: 664-670. Neonates with Down syndrome (DS) may have hematological a...
Child, Preschool Child Humans Infant, Newborn Blood Cell Count Logistic Models Risk Factors Retrospective Studies Down Syndrome Follow-Up Studies Male Female Hematologic Diseases Infant
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Overview of artificial neural network models in the biomedical domain.

Bratislavske lekarske listy Jan 1, 2019
AIM: The aim of this paper is to provide an overview of artificial neural network (ANN) in biomedical domain and compare it with the logistic regression model.
Neural Networks, Computer Logistic Models Medical Informatics Humans
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Dynamic Features Impact on the Quality of Chronic Heart Failure Predictive Modelling.

Studies in health technology and informatics Jan 1, 2019
We study the way dynamics affects modelling in chronic heart failure (CHF) tasks. By dynamics we understand the patient history and the appearance of new events, states and variables changing in time. The goal is to understand what impact past data h...
Humans Machine Learning Algorithms Forecasting Logistic Models Decision Trees Heart Failure
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Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2019
Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder affecting 1 in 59 children. While noncoding genetic variation has been shown to play a major role in many complex disorders, the contribution of these regions to ASD susceptibi...
Genetic Association Studies Computational Biology Logistic Models MicroRNAs Machine Learning Phenotype RNA, Untranslated DNA Autism Spectrum Disorder Whole Genome Sequencing Microsatellite Repeats Female Child Genetic Variation Supranuclear Palsy, Progressive CpG Islands Gene Regulatory Networks Male Humans Genetic Predisposition to Disease Case-Control Studies Cohort Studies Polymorphism, Single Nucleotide
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The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2019
Electronic phenotyping is the task of ascertaining whether an individual has a medical condition of interest by analyzing their medical record and is foundational in clinical informatics. Increasingly, electronic phenotyping is performed via supervis...
Databases, Factual Electronic Health Records Deep Learning Computational Biology Neural Networks, Computer Humans Logistic Models Machine Learning Algorithms Medical Informatics Phenotype
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