AIMC Topic: Sensitivity and Specificity

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Automatic identification of triple negative breast cancer in ultrasonography using a deep convolutional neural network.

Scientific reports
Triple negative (TN) breast cancer is a subtype of breast cancer which is difficult for early detection and the prognosis is poor. In this paper, 910 benign and 934 malignant (110 TN and 824 NTN) B-mode breast ultrasound images were collected. A Resn...

Prediction of viral symptoms using wearable technology and artificial intelligence: A pilot study in healthcare workers.

PloS one
Conventional testing and diagnostic methods for infections like SARS-CoV-2 have limitations for population health management and public policy. We hypothesize that daily changes in autonomic activity, measured through off-the-shelf technologies toget...

Artificial intelligence on COVID-19 pneumonia detection using chest xray images.

PloS one
Recent studies show the potential of artificial intelligence (AI) as a screening tool to detect COVID-19 pneumonia based on chest x-ray (CXR) images. However, issues on the datasets and study designs from medical and technical perspectives, as well a...

Deep learning on fundus images detects glaucoma beyond the optic disc.

Scientific reports
Although unprecedented sensitivity and specificity values are reported, recent glaucoma detection deep learning models lack in decision transparency. Here, we propose a methodology that advances explainable deep learning in the field of glaucoma dete...

COVID-19 Diagnosis from CT Images with Convolutional Neural Network Optimized by Marine Predator Optimization Algorithm.

BioMed research international
In recent years, almost every country in the world has struggled against the spread of Coronavirus Disease 2019. If governments and public health systems do not take action against the spread of the disease, it will have a severe impact on human life...

Artificial intelligence for detecting superficial esophageal squamous cell carcinoma under multiple endoscopic imaging modalities: A multicenter study.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Diagnosis of esophageal squamous cell carcinoma (ESCC) is complicated and requires substantial expertise and experience. This study aimed to develop an artificial intelligence (AI) system for detecting superficial ESCC under multi...

Deep convolutional neural network-based algorithm for muscle biopsy diagnosis.

Laboratory investigation; a journal of technical methods and pathology
Histopathologic evaluation of muscle biopsy samples is essential for classifying and diagnosing muscle diseases. However, the numbers of experienced specialists and pathologists are limited. Although new technologies such as artificial intelligence a...

Diagnostic test accuracy of artificial intelligence analysis of cross-sectional imaging in pulmonary hypertension: a systematic literature review.

The British journal of radiology
OBJECTIVES: To undertake the first systematic review examining the performance of artificial intelligence (AI) applied to cross-sectional imaging for the diagnosis of acquired pulmonary arterial hypertension (PAH).

Artificial Intelligence Algorithm Improves Radiologist Performance in Skeletal Age Assessment: A Prospective Multicenter Randomized Controlled Trial.

Radiology
Background Previous studies suggest that use of artificial intelligence (AI) algorithms as diagnostic aids may improve the quality of skeletal age assessment, though these studies lack evidence from clinical practice. Purpose To compare the accuracy ...

Novel Computer-Aided Diagnosis Software for the Prevention of Retained Surgical Items.

Journal of the American College of Surgeons
BACKGROUND: Retained surgical items are a serious human error. Surgical sponges account for 70% of retained surgical items. To prevent retained surgical sponges, it is important to establish a system that can identify errors and avoid the occurrence ...