AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Disease Progression

Showing 441 to 450 of 704 articles

Clear Filters

Response to repeat echoendoscopic celiac plexus neurolysis in pancreatic cancer patients: A machine learning approach.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] Jul 24, 2019
BACKGROUND: /Objectives: Efficacy of repeat echoendoscopic celiac plexus neurolysis is still unclear. Aim of the study was to assess the efficacy of repeat celiac plexus neurolysis and to build an artificial neural network model able to predict pain ...
Treatment Outcome Pancreatic Neoplasms Predictive Value of Tests Pain Measurement Pain Male Middle Aged Disease Progression Nerve Block Pain Management Endosonography Likelihood Functions Celiac Plexus Humans Machine Learning Female Aged Aged, 80 and over Adult
View on PubMed DOI

Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging.

European radiology Jul 22, 2019
BACKGROUND: We attempted to train and validate a model of deep learning for the preoperative prediction of the response of patients with intermediate-stage hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE).
Humans Retrospective Studies Tomography, X-Ray Computed Female Male Carcinoma, Hepatocellular Chemoembolization, Therapeutic Middle Aged Disease Progression Deep Learning Liver Neoplasms
View on PubMed DOI

Machine Learning-Based Predictive Modeling of Surgical Intervention in Glaucoma Using Systemic Data From Electronic Health Records.

American journal of ophthalmology Jul 16, 2019
PURPOSE: To predict the need for surgical intervention in patients with primary open-angle glaucoma (POAG) using systemic data in electronic health records (EHRs).
Glaucoma, Open-Angle Filtering Surgery Disease Progression ROC Curve Models, Statistical Odds Ratio Electronic Health Records Female Reproducibility of Results Humans Aged Aged, 80 and over Machine Learning Sensitivity and Specificity Retrospective Studies Intraocular Pressure Male Middle Aged
View on PubMed DOI

Augmented intelligence with natural language processing applied to electronic health records for identifying patients with non-alcoholic fatty liver disease at risk for disease progression.

International journal of medical informatics Jul 6, 2019
OBJECTIVE: Electronic health record (EHR) systems contain structured data (such as diagnostic codes) and unstructured data (clinical documentation). Clinical insights can be derived from analyzing both. The use of natural language processing (NLP) al...
Cohort Studies Natural Language Processing Non-alcoholic Fatty Liver Disease Electronic Health Records Female Male Middle Aged Disease Progression Humans Algorithms
View on PubMed DOI

Machine learning approaches to predict lupus disease activity from gene expression data.

Scientific reports Jul 3, 2019
The integration of gene expression data to predict systemic lupus erythematosus (SLE) disease activity is a significant challenge because of the high degree of heterogeneity among patients and study cohorts, especially those collected on different mi...
Humans Machine Learning Disease Progression Computational Biology Gene Expression Lupus Erythematosus, Systemic Gene Expression Profiling Gene Expression Regulation Transcriptome Molecular Sequence Annotation ROC Curve Gene Regulatory Networks
View on PubMed DOI

Optimized machine learning methods for prediction of cognitive outcome in Parkinson's disease.

Computers in biology and medicine Jun 28, 2019
BACKGROUND: Given the increasing recognition of the significance of non-motor symptoms in Parkinson's disease, we investigate the optimal use of machine learning methods for the prediction of the Montreal Cognitive Assessment (MoCA) score at year 4 f...
Disease Progression Longitudinal Studies Parkinson Disease Aged Models, Statistical Humans Mental Status and Dementia Tests Aged, 80 and over Machine Learning Adult Algorithms Male Female Middle Aged
View on PubMed DOI

Identifying pre-disease signals before metabolic syndrome in mice by dynamical network biomarkers.

Scientific reports Jun 24, 2019
The establishment of new therapeutic strategies for metabolic syndrome is urgently needed because metabolic syndrome, which is characterized by several disorders, such as hypertension, increases the risk of lifestyle-related diseases. One approach is...
Metabolic Syndrome Humans Models, Biological Neural Networks, Computer Symptom Assessment Phenotype Animals Biomarkers Disease Progression Mice Computational Biology
View on PubMed DOI

Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines.

Circulation. Arrhythmia and electrophysiology Jun 20, 2019
BACKGROUND: Cardiac resynchronization therapy (CRT) has significant nonresponse rates. We assessed whether machine learning (ML) could predict CRT response beyond current guidelines.
Male Ventricular Function, Left Stroke Volume Echocardiography Middle Aged Risk Assessment Disease Progression Time Factors Recovery of Function Retrospective Studies Clinical Decision-Making Female Risk Factors Aged Baltimore Humans Machine Learning Decision Support Techniques Predictive Value of Tests Patient Selection Progression-Free Survival Heart Failure Practice Guidelines as Topic Cardiac Resynchronization Therapy Heart-Assist Devices Heart Transplantation Ohio
View on PubMed DOI

Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders.

IEEE journal of biomedical and health informatics Jun 17, 2019
Many classical machine learning techniques have been used to explore Alzheimer's disease (AD), evolving from image decomposition techniques such as principal component analysis toward higher complexity, non-linear decomposition algorithms. With the a...
Humans Mental Status and Dementia Tests Algorithms Diagnosis, Computer-Assisted Deep Learning Cognitive Dysfunction Magnetic Resonance Imaging Databases, Factual Alzheimer Disease Brain Disease Progression Severity of Illness Index
View on PubMed DOI

A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data.

Alzheimer's & dementia : the journal of the Alzheimer's Association Jun 11, 2019
INTRODUCTION: It is challenging at baseline to predict when and which individuals who meet criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's disease (AD) dementia.
Hippocampus Neuroimaging Humans Disease Progression Deep Learning Dementia Magnetic Resonance Imaging Models, Neurological Alzheimer Disease Image Interpretation, Computer-Assisted
View on PubMed DOI
Popular Topics
Recent Journals