AI Medical Compendium Topic:
Middle Aged

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Development and validation of a framework for registration of whole-mount radical prostatectomy histopathology with three-dimensional transrectal ultrasound.

BMC urology
PURPOSE: Artificial intelligence (AI) has the potential to improve diagnostic imaging on multiple levels. To develop and validate these AI-assisted modalities a reliable dataset is of utmost importance. The registration of imaging to pathology is an ...

Coronary artery disease severity and location detection using deep-mining-based magnetocardiography pattern features.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The objective of this study was to develop an automated, accurate method of assessing coronary artery disease (CAD), including its severity and location, using deep-mining-based magnetocardiography (MCG) pattern features.

Automated segmentation of the dorsal root ganglia in MRI.

NeuroImage
The dorsal root ganglion (DRG) contains all primary sensory neurons, but its functional role in somatosensory and pain processing remains unclear. Recently, MR imaging techniques have been developed for objective in vivo observation of the DRG. In pa...

Deep learning-based reconstruction and superresolution for MR-guided thermal ablation of malignant liver lesions.

Cancer imaging : the official publication of the International Cancer Imaging Society
OBJECTIVE: This study evaluates the impact of deep learning-enhanced T1-weighted VIBE sequences (DL-VIBE) on image quality and procedural parameters during MR-guided thermoablation of liver malignancies, compared to standard VIBE (SD-VIBE).

Improved prediction and risk stratification of major adverse cardiovascular events using an explainable machine learning approach combining plasma biomarkers and traditional risk factors.

Cardiovascular diabetology
BACKGROUND: Cardiovascular diseases (CVD) remain the leading cause of morbidity and mortality globally. Traditional risk models, primarily based on established risk factors, often lack the precision needed to accurately predict new-onset major advers...

A validity and reliability study of the artificial intelligence attitude scale (AIAS-4) and its relationship with social media addiction and eating behaviors in Turkish adults.

BMC public health
BACKGROUND: In recent years, there has been a rapid increase in the use of the internet and social media. Billions of people worldwide use social media and spend an average of 2.2 h a day on these platforms. At the same time, artificial intelligence ...

AI feedback and workplace social support in enhancing occupational self-efficacy: a randomized controlled trial in Japan.

Scientific reports
As AI is expected to take on the role of providing workplace feedback to employees in the future, understanding how AI and humans can complement effectively in this context is crucial. This study explores this through a randomized controlled experime...

An ensemble learning model to predict lymph node metastasis in early gastric cancer.

Scientific reports
Lymph node metastasis is a critical factor for determining therapeutic strategies and assessing the prognosis of early gastric cancer. This work aimed to establish a more dependable predictive model for identify lymph node metastasis in early gastric...

Stakeholder acceptance of a robot-assisted social training scenario for autistic children compared to a tablet-computer-based approach.

Scientific reports
Recent studies indicate the potential benefits of robot-assisted therapy (RAT) for children on the autism spectrum (AS), yet acceptance among stakeholders remains unclear due to methodological shortcomings in existing research. This study evaluates s...

Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques.

Scientific reports
Ventilator-associated pneumonia significantly increases morbidity, mortality, and healthcare costs among patients with traumatic brain injury. Accurately predicting risk can facilitate earlier interventions and improve patient outcomes. This study le...