AIMC Topic: Artificial Intelligence

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Complexities of deep learning-based undersampled MR image reconstruction.

European radiology experimental
Artificial intelligence has opened a new path of innovation in magnetic resonance (MR) image reconstruction of undersampled k-space acquisitions. This review offers readers an analysis of the current deep learning-based MR image reconstruction method...

Engaging Multidisciplinary Clinical Users in the Design of an Artificial Intelligence-Powered Graphical User Interface for Intensive Care Unit Instability Decision Support.

Applied clinical informatics
BACKGROUND: Critical instability forecast and treatment can be optimized by artificial intelligence (AI)-enabled clinical decision support. It is important that the user-facing display of AI output facilitates clinical thinking and workflow for all d...

Discrepancies in the occlusal devices designed by an experienced dental laboratory technician and by 2 artificial intelligence-based automatic programs.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Artificial intelligence (AI) models have been developed for different applications, including the automatic design of occlusal devices; however, the design discrepancies of an experienced dental laboratory technician and these A...

Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions.

Diagnostic and interventional radiology (Ankara, Turkey)
With the advent of large language models (LLMs), the artificial intelligence revolution in medicine and radiology is now more tangible than ever. Every day, an increasingly large number of articles are published that utilize LLMs in radiology. To ado...

A comparative evaluation of three consecutive artificial intelligence algorithms released by Techcyte for identification of blasts and white blood cells in abnormal peripheral blood films.

International journal of laboratory hematology
INTRODUCTION: Digital pathology artificial intelligence (AI) platforms have the capacity to improve over time through "deep machine learning." We have previously reported on the accuracy of peripheral white blood cell (WBC) differential and blast ide...

Enhancing clinical reasoning with Chat Generative Pre-trained Transformer: a practical guide.

Diagnosis (Berlin, Germany)
OBJECTIVES: This study aimed to elucidate effective methodologies for utilizing the generative artificial intelligence (AI) system, namely the Chat Generative Pre-trained Transformer (ChatGPT), in improving clinical reasoning abilities among clinicia...

Letter to the Editor: Performance of ChatGPT in French language Parcours d'Accès Spécifique Santé test and in OBGYN.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics

Prediction of postoperative recurrence of oral cancer by artificial intelligence model: Multilayer perceptron.

Head & neck
BACKGROUND: Postoperative recurrence of oral cancer is an important factor affecting the prognosis of patients. Artificial intelligence is used to establish a machine learning model to predict the risk of postoperative recurrence of oral cancer.

Conserve the open media ecosystem! Legal and ethical considerations when using online repositories for AI training in ecological research.

Ecology letters
Ecological researchers who train Artificial Intelligence models using digital media have to be cognizant of legal and ethical implications when sourcing such content from online repositories. The way forward? Complying with Creative Commons licensing...

Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK.

The British journal of radiology
Technological advancements in computer science have started to bring artificial intelligence (AI) from the bench closer to the bedside. While there is still lots to do and improve, AI models in medical imaging and radiotherapy are rapidly being devel...