AI Medical Compendium Topic

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Radiologists

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A Practical Guide for AI Algorithm Selection for the Radiology Department.

Seminars in roentgenology
There is a steadily increasing number of artificial intelligence (AI) tools available and cleared for use in clinical radiological practice. Radiologists will increasingly be faced with options provided by other radiologist colleagues, clinician coll...

Introduction to Radiomics and Artificial Intelligence: A Primer for Radiologists.

Seminars in roentgenology
Health informatics and artificial intelligence (AI) are expected to transform the healthcare enterprise and the future practice of radiology. There is an increasing body of literature on radiomics and deep learning/AI applications in medical imaging....

Deep learning-based dominant index lesion segmentation for MR-guided radiation therapy of prostate cancer.

Medical physics
BACKGROUND: Dose escalation radiotherapy enables increased control of prostate cancer (PCa) but requires segmentation of dominant index lesions (DIL). This motivates the development of automated methods for fast, accurate, and consistent segmentation...

A survey of ASER members on artificial intelligence in emergency radiology: trends, perceptions, and expectations.

Emergency radiology
PURPOSE: There is a growing body of diagnostic performance studies for emergency radiology-related artificial intelligence/machine learning (AI/ML) tools; however, little is known about user preferences, concerns, experiences, expectations, and the d...

Autonomous Chest Radiograph Reporting Using AI: Estimation of Clinical Impact.

Radiology
Background Automated interpretation of normal chest radiographs could alleviate the workload of radiologists. However, the performance of such an artificial intelligence (AI) tool compared with clinical radiology reports has not been established. Pur...

Comparison of diagnostic performance of a deep learning algorithm, emergency physicians, junior radiologists and senior radiologists in the detection of appendicular fractures in children.

Pediatric radiology
BACKGROUND: Advances have been made in the use of artificial intelligence (AI) in the field of diagnostic imaging, particularly in the detection of fractures on conventional radiographs. Studies looking at the detection of fractures in the pediatric ...

Artificial Intelligence for Cardiothoracic Imaging: Overview of Current and Emerging Applications.

Seminars in roentgenology
Artificial intelligence algorithms can learn by assimilating information from large datasets in order to decipher complex associations, identify previously undiscovered pathophysiological states, and construct prediction models. There has been tremen...

Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT.

Diagnostic and interventional imaging
Artificial intelligence has demonstrated utility and is increasingly being used in the field of radiology. The use of generative pre-trained transformer (GPT)-based models has the potential to revolutionize the field of radiology, offering new possib...

Unsupervised anomaly detection for posteroanterior chest X-rays using multiresolution patch-based self-supervised learning.

Scientific reports
The demand for anomaly detection, which involves the identification of abnormal samples, has continued to increase in various domains. In particular, with increases in the data volume of medical imaging, the demand for automated screening systems has...