AIMC Topic: Adult

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Accelerated T2-weighted MRI of the Bowel at 3T Using a Single-shot Technique with Deep Learning-based Image Reconstruction: Impact on Image Quality and Disease Detection.

Academic radiology
RATIONALE AND OBJECTIVE: A single-shot T2-weighted deep-learning-based image reconstruction (DL-HASTE) has been recently developed allowing for shorter acquisition time than conventional half-Fourier acquisition single-shot turbo-spin echo (HASTE). T...

Perspectives of medical imaging professionals about the impact of AI on Swiss radiographers.

Journal of medical imaging and radiation sciences
INTRODUCTION: Artificial Intelligence (AI) is increasingly implemented in medical imaging practice, however, its impact on radiographers practice is not well studied. The aim of this study was to explore the perceived impact of AI on radiographers' a...

Developing probabilistic ensemble machine learning models for home-based sleep apnea screening using overnight SpO2 data at varying data granularity.

Sleep & breathing = Schlaf & Atmung
PURPOSE: This study aims to develop sleep apnea screening models with overnight SpO2 data, and to investigate the impact of the SpO2 data granularity on model performance.

A genetic algorithm-based method to modulate the difficulty of serious games along consecutive robot-assisted therapy sessions.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: One of the biggest challenges during neurorehabilitation therapies is finding an appropriate level of therapy intensity for each patient to ensure the recovery of movement of the affected limbs while maintaining motivation. ...

Therapeutic Exercise Recognition Using a Single UWB Radar with AI-Driven Feature Fusion and ML Techniques in a Real Environment.

Sensors (Basel, Switzerland)
Physiotherapy plays a crucial role in the rehabilitation of damaged or defective organs due to injuries or illnesses, often requiring long-term supervision by a physiotherapist in clinical settings or at home. AI-based support systems have been devel...

Machine learning prediction and explanatory models of serious infections in patients with rheumatoid arthritis treated with tofacitinib.

Arthritis research & therapy
BACKGROUND: Patients with rheumatoid arthritis (RA) have an increased risk of developing serious infections (SIs) vs. individuals without RA; efforts to predict SIs in this patient group are ongoing. We assessed the ability of different machine learn...

An artificial intelligence tool to assess the risk of severe mental distress among college students in terms of demographics, eating habits, lifestyles, and sport habits: an externally validated study using machine learning.

BMC psychiatry
BACKGROUND: Precisely estimating the probability of mental health challenges among college students is pivotal for facilitating timely intervention and preventative measures. However, to date, no specific artificial intelligence (AI) models have been...

Development and validation of a machine learning-based model to assess probability of systemic inflammatory response syndrome in patients with severe multiple traumas.

BMC medical informatics and decision making
BACKGROUND: Systemic inflammatory response syndrome (SIRS) is a predictor of serious infectious complications, organ failure, and death in patients with severe polytrauma and is one of the reasons for delaying early total surgical treatment. To deter...

Mental issues, internet addiction and quality of life predict burnout among Hungarian teachers: a machine learning analysis.

BMC public health
BACKGROUND: Burnout is usually defined as a state of emotional, physical, and mental exhaustion that affects people in various professions (e.g. physicians, nurses, teachers). The consequences of burnout involve decreased motivation, productivity, an...

Grasp and remember: the impact of human and robotic actions on object preference and memory.

Scientific reports
Goal contagion, the tendency to adopt others' goals, significantly impacts cognitive processes, which gains particular importance in the emerging field of human-robot interactions. The present study explored how observing human versus robotic actions...