AI Medical Compendium Topic:
ROC Curve

Clear Filters Showing 1141 to 1150 of 3173 articles

An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions.

European radiology
OBJECTIVES: To build an artificial intelligence (AI) system to classify benign and malignant non-mass enhancement (NME) lesions using maximum intensity projection (MIP) of early post-contrast subtracted breast MR images.

Differentiation between subchondral insufficiency fractures and advanced osteoarthritis of the knee using transfer learning and an ensemble of convolutional neural networks.

Injury
PURPOSE: Subchondral insufficiency fractures (SIF) and advanced osteoarthritis (OA) of the knee are usually seen in conjunction with bone marrow lesions (BMLs) and their differentiation may pose a significant diagnostic challenge. We aimed to develop...

A deep learning-driven low-power, accurate, and portable platform for rapid detection of COVID-19 using reverse-transcription loop-mediated isothermal amplification.

Scientific reports
This paper presents a deep learning-driven portable, accurate, low-cost, and easy-to-use device to perform Reverse-Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) to facilitate rapid detection of COVID-19. The 3D-printed device-powered...

Artificial Intelligence for Automated Implant Identification in Total Hip Arthroplasty: A Multicenter External Validation Study Exceeding Two Million Plain Radiographs.

The Journal of arthroplasty
BACKGROUND: The surgical management of complications after total hip arthroplasty (THA) necessitates accurate identification of the femoral implant manufacturer and model. Automated image processing using deep learning has been previously developed a...

A deep learning approach for detection of shallow anterior chamber depth based on the hidden features of fundus photographs.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Patients with angle-closure glaucoma (ACG) are asymptomatic until they experience a painful attack. Shallow anterior chamber depth (ACD) is considered a significant risk factor for ACG. We propose a deep learning approach t...

Deep Learning to Predict Traumatic Brain Injury Outcomes in the Low-Resource Setting.

World neurosurgery
OBJECTIVE: Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these settings, accurate patient prognostication is both difficult and essential for high-quality patient care. With the ultimate goal of ...

Incorporating Radiomics into Machine Learning Models to Predict Outcomes of Neuroblastoma.

Journal of digital imaging
Neuroblastoma is one of the most common pediatric cancers. This study used machine learning (ML) to predict the mortality and a few other investigated intermediate outcomes of neuroblastoma patients non-invasively from CT images. Performances of mult...

Detection of maxillary sinus fungal ball via 3-D CNN-based artificial intelligence: Fully automated system and clinical validation.

PloS one
BACKGROUND: This study aims to develop artificial intelligence (AI) system to automatically classify patients with maxillary sinus fungal ball (MFB), chronic rhinosinusitis (CRS), and healthy controls (HCs).

Machine learning for predicting chronic diseases: a systematic review.

Public health
OBJECTIVES: We aimed to review the literature regarding the use of machine learning to predict chronic diseases.

Artificial intelligence-based classification of bone tumors in the proximal femur on plain radiographs: System development and validation.

PloS one
PURPOSE: Early detection and classification of bone tumors in the proximal femur is crucial for their successful treatment. This study aimed to develop an artificial intelligence (AI) model to classify bone tumors in the proximal femur on plain radio...