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An international survey on AI in radiology in 1,041 radiologists and radiology residents part 1: fear of replacement, knowledge, and attitude.

European radiology
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.

Brain tissues have single-voxel signatures in multi-spectral MRI.

NeuroImage
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...

Prevalence and predictors of postoperative detrusor underactivity after robot-assisted radical prostatectomy: A prospective observational study.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To identify the prevalence and predictors of postoperative detrusor underactivity during the early postoperative period after robot-assisted radical prostatectomy.

Brain age prediction: A comparison between machine learning models using region- and voxel-based morphometric data.

Human brain mapping
Brain morphology varies across the ageing trajectory and the prediction of a person's age using brain features can aid the detection of abnormalities in the ageing process. Existing studies on such "brain age prediction" vary widely in terms of their...

Image processing and machine learning for telehealth craniosynostosis screening in newborns.

Journal of neurosurgery. Pediatrics
OBJECTIVE: The authors sought to evaluate the accuracy of a novel telehealth-compatible diagnostic software system for identifying craniosynostosis within a newborn (< 1 year old) population. Agreement with gold standard craniometric diagnostics was ...

Distant metastasis time to event analysis with CNNs in independent head and neck cancer cohorts.

Scientific reports
Deep learning models based on medical images play an increasingly important role for cancer outcome prediction. The standard approach involves usage of convolutional neural networks (CNNs) to automatically extract relevant features from the patient's...

Implementing Medical Chatbots: An Application on Hidradenitis Suppurativa.

Dermatology (Basel, Switzerland)
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 ...

Machine Learning for Prediction and Risk Stratification of Lupus Nephritis Renal Flare.

American journal of nephrology
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.

Predicting Readmission After Anterior, Posterior, and Posterior Interbody Lumbar Spinal Fusion: A Neural Network Machine Learning Approach.

World neurosurgery
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-learning based fully automatic segmentation of the globus pallidus interna and externa using ultra-high 7 Tesla MRI.

Human brain mapping
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...