AIMC Topic: Male

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Stress testing deep learning models for prostate cancer detection on biopsies and surgical specimens.

The Journal of pathology
The presence, location, and extent of prostate cancer is assessed by pathologists using H&E-stained tissue slides. Machine learning approaches can accomplish these tasks for both biopsies and radical prostatectomies. Deep learning approaches using co...

Quantitative fibrosis identifies biliary tract involvement and is associated with outcomes in pediatric autoimmune liver disease.

Hepatology communications
BACKGROUND: Children with autoimmune liver disease (AILD) may develop fibrosis-related complications necessitating a liver transplant. We hypothesize that tissue-based analysis of liver fibrosis by second harmonic generation (SHG) microscopy with art...

Towards U-Net-based intraoperative 2D dose prediction in high dose rate prostate brachytherapy.

Brachytherapy
BACKGROUND: Poor needle placement in prostate high-dose-rate brachytherapy (HDR-BT) results in sub-optimal dosimetry and mentally predicting these effects during HDR-BT is difficult, creating a barrier to widespread availability of high-quality prost...

Breath-hold diffusion-weighted MR imaging (DWI) using deep learning reconstruction: Comparison with navigator triggered DWI in patients with malignant liver tumors.

Radiography (London, England : 1995)
INTRODUCTION: This study investigated the feasibility of single breath-hold (BH) diffusion-weighted MR imaging (DWI) using deep learning reconstruction (DLR) compared to navigator triggered (NT) DWI in patients with malignant liver tumors.

Artificial Intelligence-Based Clinical Decision-Making in Erectile Dysfunction: a Narrative Review.

Current urology reports
PURPOSE OF REVIEW: Artificial Intelligence (AI) has great potential in erectile dysfunction (ED) diagnosis and treatment. This review aims to summarize AI-based clinical decision-making in ED.

Performance of automated machine learning in detecting fundus diseases based on ophthalmologic B-scan ultrasound images.

BMJ open ophthalmology
AIM: To evaluate the efficacy of automated machine learning (AutoML) models in detecting fundus diseases using ocular B-scan ultrasound images.

Integrating GPT-Based AI into Virtual Patients to Facilitate Communication Training Among Medical First Responders: Usability Study of Mixed Reality Simulation.

JMIR formative research
BACKGROUND: Training in social-verbal interactions is crucial for medical first responders (MFRs) to assess a patient's condition and perform urgent treatment during emergency medical service administration. Integrating conversational agents (CAs) in...

Digital Twin for EEG seizure prediction using time reassigned Multisynchrosqueezing transform-based CNN-BiLSTM-Attention mechanism model.

Biomedical physics & engineering express
The prediction of epileptic seizures is a classical research problem, representing one of the most challenging tasks in the analysis of brain disorders. There is active research into digital twins (DT) for various healthcare applications, as they can...

Development and validation of interpretable machine learning models for postoperative pneumonia prediction.

Frontiers in public health
BACKGROUND: Postoperative pneumonia, a prevalent form of hospital-acquired pneumonia, poses significant risks to patients' prognosis and even their lives. This study aimed to develop and validate a predictive model for postoperative pneumonia in surg...