AIMC Topic: Adult

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Artificial intelligence-powered four-fold upscaling of human brain synthetic metabolite maps.

The Journal of international medical research
ObjectiveCompared with anatomical magnetic resonance imaging modalities, metabolite images from magnetic resonance spectroscopic imaging often suffer from low quality and detail due to their larger voxel sizes. Conventional interpolation techniques a...

Estimating oxygen uptake in simulated team sports using machine learning models and wearable sensor data: A pilot study.

PloS one
Accurate assessment of training status in team sports is crucial for optimising performance and reducing injury risk. This pilot study investigates the feasibility of using machine learning (ML) models to estimate oxygen uptake (VO2) with wearable se...

Artificial intelligence prediction model for readmission after DIEP flap breast reconstruction based on NSQIP data.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: Readmissions following deep inferior epigastric perforator (DIEP) flap breast reconstruction represent a significant healthcare burden, yet current risk prediction methods lack precision in identifying high-risk patients. We developed a m...

Machine-learning guided differentiation between photoplethysmography waveforms of supraventricular and ventricular origin.

Computer methods and programs in biomedicine
BACKGROUND: It is unclear, whether photoplethysmography (PPG) waveforms from wearable devices can differentiate between supraventricular and ventricular arrhythmias. We assessed, whether a neural network-based classifier can distinguish the origin of...

A Deep Learning Survival Model for Evaluating the Survival Prognosis of Papillary Thyroid Cancer: A Population-Based Cohort Study.

Annals of surgical oncology
BACKGROUND: Deep learning can assess the individual survival prognosis in sizeable datasets with intricate underlying processes. However, studies exploring the performance of deep learning survival in papillary thyroid cancer (PTC) are lacking. This ...

X-ray based radiomics machine learning models for predicting collapse of early-stage osteonecrosis of femoral head.

Scientific reports
This study aimed to develop an X-ray radiomics model for predicting collapse of early-stage osteonecrosis of the femoral head (ONFH). A total of 87 patients (111 hips; training set: n = 67, test set: n = 44) with non-traumatic ONFH at Association Res...

Interpretable machine learning model for prediction functional cure in chronic hepatitis B patients receiving Peg-IFN therapy: A multi-center study.

International journal of medical informatics
BACKGROUND: Functional cure is the ideal treatment goal for chronic hepatitis B (CHB) treatment. We developed and validated machine learning (ML) models to predict functional cure in CHB patients.

Impact of using an AI scribe on clinical documentation and clinician-patient interactions in allied health private practice: perspectives of clinicians and patients.

Musculoskeletal science & practice
BACKGROUND: The burden associated with clinical documentation can negatively impact patient care and job satisfaction amongst allied health professionals (AHPs). Digital scribes based on artificial intelligence (AI) may address these issues, but this...

Performance of the artificial intelligence-based Swiss medical assessment system versus Manchester triage system in the emergency department: A retrospective analysis.

The American journal of emergency medicine
BACKGROUND: The emergence of artificial intelligence (AI) offers new opportunities for applications in emergency medicine, including patient triage. This study evaluates the performance of the Swiss Medical Assessment System (SMASS), an AI-based deci...