AIMC Topic: Sensitivity and Specificity

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ScreenDx, an artificial intelligence-based algorithm for the incidental detection of pulmonary fibrosis.

The American journal of the medical sciences
BACKGROUND: Nonspecific symptoms and variability in radiographic reporting patterns contribute to a diagnostic delay of the diagnosis of pulmonary fibrosis. An attractive solution is the use of machine-learning algorithms to screen for radiographic f...

Prospective External Validation of an AI-Based Emergency Department Pneumonia Disposition Prediction Tool.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
This shadow deployment evaluated an externally-developed AI tool to predict disposition using chest X-rays (CXR) in patients with community-acquired pneumonia (CAP) in the Emergency Department (ED). Retrospective and prospective external validations...

Development and validation of a machine learning approach for screening new leprosy cases based on the leprosy suspicion questionnaire.

Scientific reports
Leprosy is a dermatoneurological disease and can cause irreversible nerve damage. In addition to being able to mimic different rheumatological, neurological and dermatological diseases, leprosy is underdiagnosed because several professionals present ...

Artificial intelligence for osteoporosis detection on panoramic radiography: A systematic review and meta analysis.

Journal of dentistry
INTRODUCTION: Osteoporosis is a disease characterized by low bone mineral density and an increased risk of fractures. In dentistry, mandibular bone morphology, assessed for example on panoramic images, has been employed to detect osteoporosis. Artifi...

Continuous non-contact monitoring of neonatal activity.

BMC pediatrics
PURPOSE: Neonatal activity is an important physiological parameter in the neonatal intensive care unit (NICU). The degree of neonatal activity is associated with under and over-sedation and may also indicate the onset of disease. Activity may also ca...

A PET/CT-based 3D deep learning model for predicting spread through air spaces in stage I lung adenocarcinoma.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: This study evaluates a three-dimensional (3D) deep learning (DL) model based on fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for predicting the preoperative status of spread through air spa...

Artificial Intelligence in CT for Predicting Cervical Lymph Node Metastasis in Papillary Thyroid Cancer Patients: A Meta-analysis.

Academic radiology
PURPOSE: This meta-analysis aims to evaluate the diagnostic performance of CT-based artificial intelligence (AI) in diagnosing cervical lymph node metastasis (LNM) of papillary thyroid cancer (PTC).

Predictive utility of the machine learning algorithms in predicting tendinopathy: a meta-analysis of diagnostic test studies.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
BACKGROUND: Tendinopathy, a degenerative condition of tendon collagen protein, is a common sports injury among elite athletes. Despite its prevalence, the manifestation and progression of tendinopathy remain unclear, and the efficiency of diagnosis a...

Current State of Evidence for Use of MRI in LI-RADS.

Journal of magnetic resonance imaging : JMRI
The American College of Radiology Liver Imaging Reporting and Data System (LI-RADS) is the preeminent framework for classification and risk stratification of liver observations on imaging in patients at high risk for hepatocellular carcinoma. In this...