AIMC Topic: Sensitivity and Specificity

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Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance.

Clinical radiology
AIM: To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before passi...

ai-corona: Radiologist-assistant deep learning framework for COVID-19 diagnosis in chest CT scans.

PloS one
The development of medical assisting tools based on artificial intelligence advances is essential in the global fight against COVID-19 outbreak and the future of medical systems. In this study, we introduce ai-corona, a radiologist-assistant deep lea...

Understanding inherent image features in CNN-based assessment of diabetic retinopathy.

Scientific reports
Diabetic retinopathy (DR) is a leading cause of blindness and affects millions of people throughout the world. Early detection and timely checkups are key to reduce the risk of blindness. Automated grading of DR is a cost-effective way to ensure earl...

Domain adaptation and self-supervised learning for surgical margin detection.

International journal of computer assisted radiology and surgery
PURPOSE: One in five women who undergo breast conserving surgery will need a second revision surgery due to remaining tumor. The iKnife is a mass spectrometry modality that produces real-time margin information based on the metabolite signatures in s...

Artificial intelligence assists identifying malignant versus benign liver lesions using contrast-enhanced ultrasound.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: This study aims to construct a strategy that uses assistance from artificial intelligence (AI) to assist radiologists in the identification of malignant versus benign focal liver lesions (FLLs) using contrast-enhanced ultrasound (...

AI-based pathology predicts origins for cancers of unknown primary.

Nature
Cancer of unknown primary (CUP) origin is an enigmatic group of diagnoses in which the primary anatomical site of tumour origin cannot be determined. This poses a considerable challenge, as modern therapeutics are predominantly specific to the primar...

Development and Validation of a Deep Learning Model Using Convolutional Neural Networks to Identify Scaphoid Fractures in Radiographs.

JAMA network open
IMPORTANCE: Scaphoid fractures are the most common carpal fracture, but as many as 20% are not visible (ie, occult) in the initial injury radiograph; untreated scaphoid fractures can lead to degenerative wrist arthritis and debilitating pain, detrime...

Automated Explainable Multidimensional Deep Learning Platform of Retinal Images for Retinopathy of Prematurity Screening.

JAMA network open
IMPORTANCE: A retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy assessed by experienced ophthalmologists. A deep learning algorithm based on retinal images may facilitate early detection and timely treatment of RO...