AIMC Topic: Patient Selection

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Cohort selection for clinical trials using deep learning models.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: The goal of the 2018 n2c2 shared task on cohort selection for clinical trials (track 1) is to identify which patients meet the selection criteria for clinical trials. Cohort selection is a particularly demanding task to which natural langu...
Patient Selection Data Mining Clinical Trials as Topic Neural Networks, Computer Deep Learning Natural Language Processing Humans
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Evaluating shallow and deep learning strategies for the 2018 n2c2 shared task on clinical text classification.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: Automated clinical phenotyping is challenging because word-based features quickly turn it into a high-dimensional problem, in which the small, privacy-restricted, training datasets might lead to overfitting. Pretrained embeddings might sol...
Classification Patient Selection Data Mining Clinical Trials as Topic Deep Learning Logistic Models Natural Language Processing Humans Neural Networks, Computer Machine Learning
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Medical knowledge infused convolutional neural networks for cohort selection in clinical trials.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: In this era of digitized health records, there has been a marked interest in using de-identified patient records for conducting various health related surveys. To assist in this research effort, we developed a novel clinical data represent...
Patient Selection Data Mining Clinical Trials as Topic Humans Neural Networks, Computer Deep Learning Support Vector Machine Natural Language Processing
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Cohort selection for clinical trials using hierarchical neural network.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: Cohort selection for clinical trials is a key step for clinical research. We proposed a hierarchical neural network to determine whether a patient satisfied selection criteria or not.
Humans Neural Networks, Computer Machine Learning Patient Selection Data Mining Clinical Trials as Topic Electronic Health Records Mental Health Natural Language Processing Electronic Data Processing
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Clinical trial cohort selection based on multi-level rule-based natural language processing system.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: Identifying patients who meet selection criteria for clinical trials is typically challenging and time-consuming. In this article, we describe our clinical natural language processing (NLP) system to automatically assess patients' eligibil...
Data Mining Clinical Trials as Topic Deep Learning Natural Language Processing Patient Selection Humans Neural Networks, Computer
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Hybrid bag of approaches to characterize selection criteria for cohort identification.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: The 2018 National NLP Clinical Challenge (2018 n2c2) focused on the task of cohort selection for clinical trials, where participating systems were tasked with analyzing longitudinal patient records to determine if the patients met or did n...
Data Mining Pattern Recognition, Automated Clinical Trials as Topic Humans Machine Learning Natural Language Processing Patient Selection
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Optimizing clinical trials recruitment via deep learning.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: Clinical trials, prospective research studies on human participants carried out by a distributed team of clinical investigators, play a crucial role in the development of new treatments in health care. This is a complex and expensive proce...
Humans Databases, Factual Electronic Health Records Research Personnel Clinical Trials as Topic Insurance Claim Reporting Deep Learning Patient Selection Data Mining
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Use of Artificial Intelligence to Represent Emergent Systems and Augment Surgical Decision-making.

JAMA surgery Sep 1, 2019
Female Male Risk Assessment Emergencies United States Patient Selection Artificial Intelligence Intensive Care Units Clinical Decision-Making Humans Surgical Procedures, Operative Surgery Department, Hospital
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Impact of Artificial Intelligence on Interventional Cardiology: From Decision-Making Aid to Advanced Interventional Procedure Assistance.

JACC. Cardiovascular interventions Jul 22, 2019
Access to big data analyzed by supercomputers using advanced mathematical algorithms (i.e., deep machine learning) has allowed for enhancement of cognitive output (i.e., visual imaging interpretation) to previously unseen levels and promises to funda...
Therapy, Computer-Assisted Cardiac Catheterization Diagnosis, Computer-Assisted Deep Learning Unsupervised Machine Learning Decision Support Techniques Clinical Decision-Making Cardiovascular Diseases Supervised Machine Learning Patient Selection Diffusion of Innovation Predictive Value of Tests Robotics Workflow Humans Machine Learning
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Criteria2Query: a natural language interface to clinical databases for cohort definition.

Journal of the American Medical Informatics Association : JAMIA Apr 1, 2019
OBJECTIVE: Cohort definition is a bottleneck for conducting clinical research and depends on subjective decisions by domain experts. Data-driven cohort definition is appealing but requires substantial knowledge of terminologies and clinical data mode...
Databases as Topic Information Storage and Retrieval Clinical Trials as Topic Eligibility Determination User-Computer Interface Natural Language Processing Patient Selection Humans Machine Learning
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