AI Medical Compendium Topic:
Radiology

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Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning.

Korean journal of radiology
Artificial intelligence has been applied to many industries, including medicine. Among the various techniques in artificial intelligence, deep learning has attained the highest popularity in medical imaging in recent years. Many articles on deep lear...

[Machine learning in radiology : Terminology from individual timepoint to trajectory].

Der Radiologe
METHODICAL ISSUE: Machine learning (ML) algorithms have an increasingly relevant role in radiology tackling tasks such as the automatic detection and segmentation of diagnosis-relevant markers, the quantification of progression and response, and thei...

[Artificial Intelligence in radiology : What can be expected in the next few years?].

Der Radiologe
CLINICAL/METHODOLOGICAL ISSUE: Artificial intelligence (AI) is being increasingly used in the field of radiology. The aim of this review is to illustrate the developments expected in the next 5 to 10 years as well as possible advantages and risks.

Augmented Radiologist Workflow Improves Report Value and Saves Time: A Potential Model for Implementation of Artificial Intelligence.

Academic radiology
RATIONALE AND OBJECTIVES: Our primary aim was to improve radiology reports by increasing concordance of target lesion measurements with oncology records using radiology preprocessors (RP). Faster notification of incidental actionable findings to refe...

How the FDA Regulates AI.

Academic radiology
Recent years have seen digital technologies increasingly leveraged to multiply conventional imaging modalities' diagnostic power. Artificial intelligence (AI) is most prominent among these in the radiology space, touted as the "stethoscope of the 21s...

School of Block-Review of Blockchain for the Radiologists.

Academic radiology
Blockchain, the underlying technology for Bitcoin, is a distributed digital ledger technology that enables record verification by many independent parties rather than a centralized authority, therefore making it more difficult to tamper with the data...

A Review of Perceptual Expertise in Radiology-How it develops, How we can test it, and Why humans still matter in the era of Artificial Intelligence.

Academic radiology
As the first step in image interpretation is detection, an error in perception can prematurely end the diagnostic process leading to missed diagnoses. Because perceptual errors of this sort-"failure to detect"-are the most common interpretive error (...

Impact of the Artificial Nudge.

Academic radiology
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) is playing a growing role in the field of radiology. This article seeks to help readers quantify its impact when put into practice, using a lung nodule flagger as an example.

The Algorithmic Audit: Working with Vendors to Validate Radiology-AI Algorithms-How We Do It.

Academic radiology
There is a plethora of Artificial Intelligence (AI) tools that are being developed around the world aiming at either speeding up or improving the accuracy of radiologists. It is essential for radiologists to work with the developers of such algorithm...