AIMC Topic: Sensitivity and Specificity

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Accurate Identification of Colonoscopy Quality and Polyp Findings Using Natural Language Processing.

Journal of clinical gastroenterology
OBJECTIVES: The aim of this study was to test the ability of a commercially available natural language processing (NLP) tool to accurately extract examination quality-related and large polyp information from colonoscopy reports with varying report fo...

[An artificial neural network model for glioma grading using image information].

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
To explore the feasibility and efficacy of artificial neural network for differentiating high-grade glioma and low-grade glioma using image information.
 Methods: A total of 130 glioma patients with confirmed pathological diagnosis were selected retr...

Improving Detection of Early Chronic Obstructive Pulmonary Disease.

Annals of the American Thoracic Society
Despite being a major cause of morbidity and mortality, chronic obstructive pulmonary disease (COPD) is frequently undiagnosed. Yet the burden of disease among the undiagnosed is significant, as these individuals experience symptoms, exacerbations, a...

Comparison of Natural Language Processing and Manual Coding for the Identification of Cross-Sectional Imaging Reports Suspicious for Lung Cancer.

JCO clinical cancer informatics
PURPOSE: To compare the accuracy and reliability of a natural language processing (NLP) algorithm with manual coding by radiologists, and the combination of the two methods, for the identification of patients whose computed tomography (CT) reports ra...

Machine Learning Outperforms ACC / AHA CVD Risk Calculator in MESA.

Journal of the American Heart Association
Background Studies have demonstrated that the current US guidelines based on American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Equations Risk Calculator may underestimate risk of atherosclerotic cardiovascular disease ...

[COLONSCORE: THE USE OF MACHINE LEARNING OF BIG DATA TO DETECT COLORECTAL CANCER].

Harefuah
The use of big data is in its first years of entering the medical world. Big data research enables analysis of very large volumes of data, identifying patterns and findings which traditional statistical methods cannot handle. The diagnosis of colorec...

3D deep learning for detecting pulmonary nodules in CT scans.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To demonstrate and test the validity of a novel deep-learning-based system for the automated detection of pulmonary nodules.

Deep Learning-Based Computer-Aided Diagnosis System for Localization and Diagnosis of Metastatic Lymph Nodes on Ultrasound: A Pilot Study.

Thyroid : official journal of the American Thyroid Association
BACKGROUND: The presence of metastatic lymph nodes is a prognostic indicator for patients with thyroid carcinomas and is an important determinant of clinical decision making. However, evaluating neck lymph nodes requires experience and is labor- and ...

Unique Clinical Language Patterns Among Expert Vestibular Providers Can Predict Vestibular Diagnoses.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
OBJECTIVE: To identify novel language usage by expert providers predictive of specific vestibular conditions.