OBJECTIVES: Radiologists' perception is likely to influence the adoption of artificial intelligence (AI) into clinical practice. We investigated knowledge and attitude towards AI by radiologists and residents in Europe and beyond.
Since the seminal works by Brodmann and contemporaries, it is well-known that different brain regions exhibit unique cytoarchitectonic and myeloarchitectonic features. Transferring the approach of classifying brain tissues - and other tissues - based...
Anaesthesia, critical care & pain medicine
Mar 20, 2021
INTRODUCTION: Paediatric robotic surgery is gaining popularity across multiple disciplines and offers technical advantages in complex procedures requiring delicate dissection. To date, limited publications describe its perioperative management in chi...
OBJECTIVE: To analyze and compare the imaging workflow, radiation dose, and image quality for COVID-19 patients examined using either the conventional manual positioning (MP) method or an AI-based automatic positioning (AP) method.
Smartphone applications ("apps") with artificial intelligence (AI) algorithms are increasingly used in healthcare. Widespread adoption of these apps must be supported by a robust evidence-base and app manufacturers' claims appropriately regulated. Cu...
BACKGROUND: The use of digital health resources is growing quickly as they are easily accessible and permit self-evaluation. Yet, research on consumer health informatics platforms is insufficient. Chatbots, interactive conversational platforms based ...
BACKGROUND: Renal flare of lupus nephritis (LN) is strongly associated with poor kidney outcomes, and predicting renal flare and stratifying its risk are important for clinical decision-making and individualized management to reduce LN flare.
BACKGROUND: Readmission after spine surgery is costly and a relatively common occurrence. Previous research identified several risk factors for readmission; however, the conclusions remain equivocal. Machine learning algorithms offer a unique perspec...
Deep brain stimulation (DBS) surgery has been shown to dramatically improve the quality of life for patients with various motor dysfunctions, such as those afflicted with Parkinson's disease (PD), dystonia, and essential tremor (ET), by relieving mot...
OBJECTIVE: The aim of this study was to evaluate the feasibility of machine learning based on diffusion tensor imaging (DTI) measures to distinguish patients with focal epilepsy versus healthy controls and antiseizure medication (ASM) responsiveness.
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