AIMC Topic: Clinical Trials as Topic

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Machine Learning Predictive Models Can Improve Efficacy of Clinical Trials for Alzheimer's Disease.

Journal of Alzheimer's disease : JAD Jan 1, 2020
BACKGROUND: The ideal participants for Alzheimer's disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e., placebo arm) and also would be responsive to the therapeutic intervention being studied (i.e., drug arm). ...
Algorithms Research Design Databases, Factual Female Humans Machine Learning Sensitivity and Specificity Male Cognitive Dysfunction Follow-Up Studies Reproducibility of Results Aged Aged, 80 and over Mental Status and Dementia Tests Alzheimer Disease Neuroimaging Clinical Trials as Topic Clinical Trials, Phase III as Topic Magnetic Resonance Imaging Predictive Value of Tests Sample Size
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Artificial Intelligence Tool for Optimizing Eligibility Screening for Clinical Trials in a Large Community Cancer Center.

JCO clinical cancer informatics Jan 1, 2020
PURPOSE: Less than 5% of patients with cancer enroll in clinical trials, and 1 in 5 trials are stopped for poor accrual. We evaluated an automated clinical trial matching system that uses natural language processing to extract patient and trial chara...
Early Detection of Cancer Natural Language Processing Patient Selection Humans Clinical Trials as Topic Artificial Intelligence Machine Learning Adult Eligibility Determination Female Breast Neoplasms Community Networks Aged Middle Aged Aged, 80 and over
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Clinical Practice Settings vs Clinical Trials: Is Artificial Intelligence the Answer?

JAMA ophthalmology Jan 1, 2020
Machine Learning Diagnosis, Computer-Assisted Clinical Trials as Topic Professional Practice Humans Artificial Intelligence
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Sodium glucose co-transporter 2 inhibitors and cardiovascular event protections: how applicable are clinical trials and observational studies to real-world patients?

BMJ open diabetes research & care Dec 1, 2019
OBJECTIVE: This study evaluated the characteristics of new users of sodium glucose co-transporter 2 inhibitors (SGLT2i) in clinical practice to assess the applicability of the findings from clinical trials (Empagliflozin, Cardiovascular Outcomes and ...
Bridged Bicyclo Compounds, Heterocyclic Aged Canagliflozin Cardiovascular Diseases Humans Clinical Trials as Topic Aged, 80 and over Middle Aged Retrospective Studies Cohort Studies Diabetic Angiopathies Adult Blood Glucose Female Diabetes Mellitus, Type 2 Glucosides Male Sodium-Glucose Transporter 2 Inhibitors Observational Studies as Topic Benzhydryl Compounds Practice Patterns, Physicians' Glycated Hemoglobin
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Cohort selection for clinical trials: n2c2 2018 shared task track 1.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: Track 1 of the 2018 National NLP Clinical Challenges shared tasks focused on identifying which patients in a corpus of longitudinal medical records meet and do not meet identified selection criteria.
Natural Language Processing Clinical Trials as Topic Humans Patient Selection Data Mining Machine Learning Datasets as Topic
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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...
Clinical Trials as Topic Deep Learning Natural Language Processing Patient Selection Data Mining Humans Neural Networks, Computer
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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...
Humans Neural Networks, Computer Machine Learning Deep Learning Logistic Models Natural Language Processing Classification Patient Selection Data Mining Clinical Trials as Topic
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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...
Support Vector Machine Humans Natural Language Processing Neural Networks, Computer Patient Selection Deep Learning Data Mining Clinical Trials as Topic
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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.
Electronic Data Processing Natural Language Processing Patient Selection Data Mining Clinical Trials as Topic Machine Learning Electronic Health Records Mental Health Humans Neural Networks, Computer
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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...
Clinical Trials as Topic Humans Neural Networks, Computer Deep Learning Natural Language Processing Patient Selection Data Mining
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