AIMC Topic: Sensitivity and Specificity

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AIBx, Artificial Intelligence Model to Risk Stratify Thyroid Nodules.

Thyroid : official journal of the American Thyroid Association Mar 11, 2020
Current classification systems for thyroid nodules are very subjective. Artificial intelligence (AI) algorithms have been used to decrease subjectivity in medical image interpretation. One out of 2 women over the age of 50 years may have a thyroid n...
Carcinoma, Papillary, Follicular Sensitivity and Specificity Humans Risk Assessment Artificial Intelligence Ultrasonography Algorithms Thyroid Gland Thyroid Nodule Thyroid Neoplasms Image Interpretation, Computer-Assisted Adenocarcinoma, Follicular Thyroid Cancer, Papillary
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Semi-Supervised Nests of Melanocytes Segmentation Method Using Convolutional Autoencoders.

Sensors (Basel, Switzerland) Mar 11, 2020
In this research, we present a semi-supervised segmentation solution using convolutional autoencoders to solve the problem of segmentation tasks having a small number of ground-truth images. We evaluate the proposed deep network architecture for the ...
Supervised Machine Learning Melanoma Image Interpretation, Computer-Assisted Sensitivity and Specificity Nevus Deep Learning Melanocytes Skin Humans Algorithms
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Monitoring Glaucomatous Functional Loss Using an Artificial Intelligence-Enabled Dashboard.

Ophthalmology Mar 10, 2020
PURPOSE: To develop an artificial intelligence (AI) dashboard for monitoring glaucomatous functional loss.
Humans Glaucoma Artificial Intelligence Retrospective Studies Cross-Sectional Studies Male Middle Aged Longitudinal Studies Monitoring, Physiologic Female Aged Adult Sensitivity and Specificity False Negative Reactions Optic Nerve Diseases Visual Acuity Vision Disorders Predictive Value of Tests Visual Fields
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A pilot trial of Convolution Neural Network for automatic retention-monitoring of capsule endoscopes in the stomach and duodenal bulb.

Scientific reports Mar 5, 2020
The retention of a capsule endoscope (CE) in the stomach and the duodenal bulb during the examination is a troublesome problem, which can make the medical staff spend several hours observing whether the CE enters the descending segment of the duodenu...
Neural Networks, Computer Algorithms Retrospective Studies Female Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity Humans Capsule Endoscopes Foreign Bodies Image Processing, Computer-Assisted Male Duodenum Middle Aged Automation Adolescent Capsule Endoscopy Monitoring, Intraoperative Stomach
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Using Natural Language Processing to improve EHR Structured Data-based Surgical Site Infection Surveillance.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Surgical Site Infection surveillance in healthcare systems is labor intensive and plagued by underreporting as current methodology relies heavily on manual chart review. The rapid adoption of electronic health records (EHRs) has the potential to allo...
Natural Language Processing Humans Sensitivity and Specificity Machine Learning Logistic Models Algorithms Support Vector Machine Surgical Wound Infection Electronic Health Records Decision Trees Information Storage and Retrieval
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Deep Learning from Incomplete Data: Detecting Imminent Risk of Hospital-acquired Pneumonia in ICU Patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Hospital acquired pneumonia (HAP) is the second most common nosocomial infection in the ICU and costs an estimated $3.1 billion annually. The ability to predict HAP could improve patient outcomes and reduce costs. Traditional pneumonia risk predictio...
Intensive Care Units Humans Sensitivity and Specificity Risk Assessment Deep Learning Healthcare-Associated Pneumonia
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Comparing machine and human reviewers to evaluate the risk of bias in randomized controlled trials.

Research synthesis methods Mar 3, 2020
BACKGROUND: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can...
Pattern Recognition, Automated Risk Randomized Controlled Trials as Topic Bias Outcome Assessment, Health Care Observer Variation Humans Machine Learning Software Reproducibility of Results Sensitivity and Specificity Risk Assessment Health Policy
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Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms.

JAMA network open Mar 2, 2020
IMPORTANCE: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives.
Female Sweden Aged Adult Sensitivity and Specificity Humans Artificial Intelligence Algorithms Early Detection of Cancer Mammography Radiology Radiologists Breast Neoplasms Image Interpretation, Computer-Assisted Middle Aged Deep Learning United States
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CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.

European radiology Feb 28, 2020
PURPOSE: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma. The aims of this study are to develop and validate a computed tomography ...
Female Risk Factors Sensitivity and Specificity Neoplasm Invasiveness Male ROC Curve Humans Neoplasm Recurrence, Local Middle Aged Machine Learning Image Processing, Computer-Assisted Adenocarcinoma of Lung Retrospective Studies Lung Neoplasms Tomography, X-Ray Computed Logistic Models
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Calculating the target exposure index using a deep convolutional neural network and a rule base.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Feb 27, 2020
PURPOSE: The objective of this study is to determine the quality of chest X-ray images using a deep convolutional neural network (DCNN) and a rule base without performing any visual assessment. A method is proposed for determining the minimum diagnos...
Mediastinum Image Processing, Computer-Assisted Spine Radiography, Thoracic Thorax Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity Middle Aged Lung Deep Learning Humans Neural Networks, Computer Tomography, X-Ray Computed
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