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Deep learning and conventional hip MRI for the detection of labral and cartilage abnormalities using arthroscopy as standard of reference.

European radiology
OBJECTIVES: To evaluate the performance of high-resolution deep learning-based hip MR imaging (CSAI) compared to standard-resolution compressed sense (CS) sequences using hip arthroscopy as standard of reference.

The impact of ChatGPT on nursing education: A qualitative study based on the experiences of faculty members.

Nurse education today
BACKGROUND: Recent advancements in artificial intelligence technologies particularly ChatGPT have supported learning and fostered critical thinking in nursing education. However, integrating these tools into academic settings requires both ethical an...

Quantification of physiological crystalline Lens decentration using swept source OCT.

European journal of ophthalmology
PurposeTo quantify the decentration of the crystalline lens in a large Austrian adult cataractous and non-cataractous cohort and to predict decentration using biometric parameters.SettingKepler University Clinic, Linz, Austria.DesignRetrospective sin...

Using machine learning and electronic health record (EHR) data for the early prediction of Alzheimer's Disease and Related Dementias.

The journal of prevention of Alzheimer's disease
BACKGROUND: Over 6 million patients in the United States are affected by Alzheimer's Disease and Related Dementias (ADRD). Early detection of ADRD can significantly improve patient outcomes through timely treatment.

Prediction of Tumor Budding Grading in Rectal Cancer Using a Multiparametric MRI Radiomics Combined with a 3D Vision Transformer Deep Learning Approach.

Academic radiology
RATIONALE AND OBJECTIVES: The objective is to assess the effectiveness of a multiparametric MRI radiomics strategy combined with a 3D Vision Transformer (ViT) deep learning (DL) model in predicting tumor budding (TB) grading in individuals diagnosed ...

Controlled Pilot Intervention Study on the Effects of an AI-Based Application to Support Incontinence-Associated Dermatitis and Pressure Injury Assessment, Nursing Care and Documentation: Study Protocol.

Research in nursing & health
Artificial Intelligence (AI)-based applications have significant potential to differentiate between pressure injuries (PI) and incontinence-associated dermatitis (IAD), common challenges in nursing practice. Within the KIADEKU overall project, we are...

Deep learning-based EEG source imaging is robust under varying electrode configurations.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVES: Previous research has underscored the necessity of high-density EEG for accurate and reliable EEG source imaging (ESI) results with conventional ESI methods, limiting their utility in clinical settings with only low-density EEG available....

Assessment of AI-accelerated T2-weighted brain MRI, based on clinical ratings and image quality evaluation.

European journal of radiology
OBJECTIVE: To compare clinical ratings and signal-to-noise ratio (SNR) measures of a commercially available Deep Learning-based MRI reconstruction method (T2) against conventional T2- turbo spin echo brain MRI (T2).

Comparison of CNNs and Transformer Models in Diagnosing Bone Metastases in Bone Scans Using Grad-CAM.

Clinical nuclear medicine
PURPOSE: Convolutional neural networks (CNNs) have been studied for detecting bone metastases on bone scans; however, the application of ConvNeXt and transformer models has not yet been explored. This study aims to evaluate the performance of various...