AIMC Topic: Clinical Trials as Topic

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Follow-Up on the Use of Machine Learning in Clinical Quality Assurance: Can We Detect Adverse Event Under-Reporting in Oncology Trials?

Drug safety Mar 1, 2020
Humans Machine Learning Patient Safety Quality Assurance, Health Care Quality Indicators, Health Care Clinical Trials as Topic Adverse Drug Reaction Reporting Systems Neoplasms Antineoplastic Agents Drug-Related Side Effects and Adverse Reactions Research Report
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Retrospective imaging studies of gastric cancer: Study protocol clinical trial (SPIRIT Compliant).

Medicine Feb 1, 2020
INTRODUCTION: Peritoneal metastasis (PM) is a frequent condition in patients presenting with gastric cancer, especially in younger patients with advanced tumor stages. Computer tomography (CT) is the most common noninvasive modality for preoperative ...
Clinical Trials as Topic Sensitivity and Specificity Image Processing, Computer-Assisted Peritoneal Neoplasms Humans Machine Learning Artificial Intelligence Retrospective Studies Tomography, X-Ray Computed Stomach Neoplasms
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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). ...
Clinical Trials as Topic Clinical Trials, Phase III as Topic Mental Status and Dementia Tests Cognitive Dysfunction Follow-Up Studies Magnetic Resonance Imaging Humans Predictive Value of Tests Aged Sample Size Databases, Factual Alzheimer Disease Machine Learning Aged, 80 and over Female Neuroimaging Algorithms Sensitivity and Specificity Research Design Reproducibility of Results Male
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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...
Humans Artificial Intelligence Machine Learning Female Middle Aged Early Detection of Cancer Natural Language Processing Patient Selection Aged Aged, 80 and over Adult Breast Neoplasms Clinical Trials as Topic Eligibility Determination Community Networks
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Clinical Practice Settings vs Clinical Trials: Is Artificial Intelligence the Answer?

JAMA ophthalmology Jan 1, 2020
Humans Clinical Trials as Topic Professional Practice Artificial Intelligence Machine Learning Diagnosis, Computer-Assisted
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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 Canagliflozin Cardiovascular Diseases Aged Middle Aged Humans Aged, 80 and over Clinical Trials as Topic Cohort Studies Blood Glucose Sodium-Glucose Transporter 2 Inhibitors Adult Retrospective Studies Diabetic Angiopathies Diabetes Mellitus, Type 2 Glucosides Male Observational Studies as Topic Female Benzhydryl Compounds Glycated Hemoglobin Practice Patterns, Physicians'
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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.
Patient Selection Data Mining Datasets as Topic Clinical Trials as Topic Humans Machine Learning Natural Language Processing
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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...
Natural Language Processing Patient Selection Data Mining Clinical Trials as Topic Humans Neural Networks, Computer Deep Learning
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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 Patient Selection Data Mining Clinical Trials as Topic Classification
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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...
Natural Language Processing Patient Selection Data Mining Clinical Trials as Topic Humans Neural Networks, Computer Deep Learning Support Vector Machine
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