AIMC Topic:
Predictive Value of Tests

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Predicting hospital readmission for lupus patients: An RNN-LSTM-based deep-learning methodology.

Computers in biology and medicine Aug 31, 2018
Hospital readmission is one of the critical metrics used for measuring the performance of hospitals. The HITECH Act imposes penalties when patients are readmitted to hospitals if they are diagnosed with one of the six conditions mentioned in the Act....
Deep Learning Predictive Value of Tests Lupus Erythematosus, Systemic Models, Biological Patient Readmission Humans Neural Networks, Computer Female Male
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Identifying people at risk of developing type 2 diabetes: A comparison of predictive analytics techniques and predictor variables.

International journal of medical informatics Aug 28, 2018
BACKGROUND: The present study aims to identify the patients at risk of type 2 diabetes (T2D). There is a body of literature that uses machine learning classification algorithms to predict development of T2D among patients. The current study compares ...
Humans Neural Networks, Computer Female Risk Factors Male Machine Learning Algorithms Mass Screening Support Vector Machine Predictive Value of Tests Middle Aged Disease Progression Diabetes Mellitus, Type 2 Logistic Models
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Predictive connectome subnetwork extraction with anatomical and connectivity priors.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Aug 25, 2018
We present a new method to identify anatomical subnetworks of the human connectome that are optimally predictive of targeted clinical variables, developmental outcomes or disease states. Given a training set of structural or functional brain networks...
Infant, Premature Connectome Magnetic Resonance Imaging Predictive Value of Tests Anatomic Landmarks Autistic Disorder Humans Machine Learning Infant, Newborn
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Application of machine-learning to predict early spontaneous preterm birth among nulliparous non-Hispanic black and white women.

Annals of epidemiology Aug 24, 2018
PURPOSE: Spontaneous preterm birth is a leading cause of perinatal mortality in the United States, occurring disproportionately among non-Hispanic black women compared to other race-ethnicities. Clinicians lack tools to identify first-time mothers at...
Gestational Age Machine Learning California Black or African American Retrospective Studies Birth Certificates Pregnancy Humans Female Premature Birth ROC Curve Parity Predictive Value of Tests White People
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The utility of artificial neural networks and classification and regression trees for the prediction of endometrial cancer in postmenopausal women.

Public health Aug 24, 2018
OBJECTIVE: Artificial neural networks (ANNs) and classification and regression trees (CARTs) have been previously used for the prediction of cancer in several fields. In our study, we aim to investigate the diagnostic accuracy of three different meth...
Regression Analysis Decision Trees Predictive Value of Tests Postmenopause Reproducibility of Results Aged Middle Aged Case-Control Studies Endometrial Neoplasms Neural Networks, Computer Retrospective Studies Female Humans
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Exploiting MEDLINE for gene molecular function prediction via NMF based multi-label classification.

Journal of biomedical informatics Aug 18, 2018
Gene ontology (GO) provides a representation of terms and categories used to describe genes and their molecular functions, cellular components and biological processes. GO has been the standard for describing the functions of specific genes in differ...
Animals Computational Biology Databases, Genetic Models, Statistical Decision Trees Humans Algorithms Reproducibility of Results Molecular Sequence Annotation Gene Ontology Databases, Protein Predictive Value of Tests Markov Chains MEDLINE
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Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks.

Gastrointestinal endoscopy Aug 16, 2018
BACKGROUND AND AIMS: The prognosis of esophageal cancer is relatively poor. Patients are usually diagnosed at an advanced stage when it is often too late for effective treatment. Recently, artificial intelligence (AI) using deep learning has made rem...
Carcinoma, Squamous Cell Aged Aged, 80 and over Sensitivity and Specificity Neural Networks, Computer Artificial Intelligence Retrospective Studies Female Adenocarcinoma Predictive Value of Tests Esophageal Neoplasms Japan Tumor Burden Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Humans
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Automated Cardiac MR Scar Quantification in Hypertrophic Cardiomyopathy Using Deep Convolutional Neural Networks.

JACC. Cardiovascular imaging Aug 15, 2018
Magnetic Resonance Imaging Predictive Value of Tests Cicatrix Myocardium Automation Image Interpretation, Computer-Assisted Humans Cardiomyopathy, Hypertrophic Proof of Concept Study Deep Learning
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Artificial neural networks help to identify disease subsets and to predict lymphoma in primary Sjögren's syndrome.

Clinical and experimental rheumatology Aug 14, 2018
OBJECTIVES: Primary Sjögren's syndrome (pSS) is a complex chronic systemic disorder, for which specific and effective therapeutic interventions are still lacking. In this era of precision medicine, there is a clear need for a better definition of dis...
Aged Humans Male Middle Aged Neural Networks, Computer Prognosis Disease Progression Decision Support Techniques Predictive Value of Tests Female Phenotype Severity of Illness Index Sjogren's Syndrome Principal Component Analysis Reproducibility of Results Biomarkers Diagnosis, Computer-Assisted Risk Factors Lymphoma Autoantibodies Diagnosis, Differential Data Mining Serologic Tests
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Exploring the prediction of emotional valence and pharmacologic effect across fMRI studies of antidepressants.

NeuroImage. Clinical Aug 11, 2018
BACKGROUND: Clinically approved antidepressants modulate the brain's emotional valence circuits, suggesting that the response of these circuits could serve as a biomarker for screening candidate antidepressant drugs. However, it is necessary that the...
Psychomotor Performance Treatment Outcome Humans Magnetic Resonance Imaging Antidepressive Agents Machine Learning Emotions Photic Stimulation Predictive Value of Tests Databases, Factual Brain
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