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Artificial intelligence assisted whole organ pancreatic fat estimation on magnetic resonance imaging and correlation with pancreas attenuation on computed tomography.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
BACKGROUND: Fatty pancreas is associated with inflammatory and neoplastic pancreatic diseases. Magnetic resonance imaging (MRI) is the diagnostic modality of choice for measuring pancreatic fat. Measurements typically use regions of interest limited ...

The diagnosis of femoroacetabular impingement can be made on pelvis radiographs using deep learning methods.

Joint diseases and related surgery
OBJECTIVES: The aim of this study was to evaluate diagnostic ability of deep learning models, particularly convolutional neural network models used for image classification, for femoroacetabular impingement (FAI) using hip radiographs.

A deep learning-based approach for statistical robustness evaluation in proton therapy treatment planning: a feasibility study.

Physics in medicine and biology
. Robustness evaluation is critical in particle radiotherapy due to its susceptibility to uncertainties. However, the customary method for robustness evaluation only considers a few uncertainty scenarios, which are insufficient to provide a consisten...

Deep learning enables MV-based real-time image guided radiation therapy for prostate cancer patients.

Physics in medicine and biology
. Using MV images for real-time image guided radiation therapy (IGRT) is ideal as it does not require additional imaging equipment, adds no additional imaging dose and provides motion data in the treatment beam frame of reference. However, accurate t...

Comparison of postoperative urinary continence and incontinence types between conventional and Retzius-sparing robot-assisted radical prostatectomy.

Neurourology and urodynamics
AIMS: This study aimed to investigate the postoperative urinary continence rate and incontinence types compared over time between conventional robot-assisted radical prostatectomy (C-RARP) and Retzius-sparing RARP (RS-RARP).

Evaluation of a deep learning-enabled automated computational heart modelling workflow for personalized assessment of ventricular arrhythmias.

The Journal of physiology
Personalized, image-based computational heart modelling is a powerful technology that can be used to improve patient-specific arrhythmia risk stratification and ventricular tachycardia (VT) ablation targeting. However, most state-of-the-art methods s...

Using artificial intelligence to reduce orthopedic surgical site infection surveillance workload: Algorithm design, validation, and implementation in 4 Spanish hospitals.

American journal of infection control
BACKGROUND: Surgical site infection (SSI) surveillance is a labor-intensive endeavor. We present the design and validation of an algorithm for SSI detection after hip replacement surgery, and a report of its successful implementation in 4 public hosp...

Effect of radiotherapy on phagocytosis percentage and index in patients with oral squamous cell carcinoma.

Journal of cancer research and therapeutics
BACKGROUND: Phagocytosis plays an important role in the fundamental process of immunity and maintains systemic tissue homeostasis. Phagocytosis function is assessed in radiotherapy to signify the prognosis of patient. Therefore, we designed a study t...

Assessment of Awareness, Perceptions, and Opinions towards Artificial Intelligence among Healthcare Students in Riyadh, Saudi Arabia.

Medicina (Kaunas, Lithuania)
: The role of the pharmacist in healthcare society is unique, since they are providers of health information and medication counseling to patients. Hence, this study aimed to evaluate Awareness, Perceptions, and Opinions towards Artificial intelligen...

Effects of deep learning on radiologists' and radiology residents' performance in identifying esophageal cancer on CT.

The British journal of radiology
OBJECTIVE: To investigate the effectiveness of a deep learning model in helping radiologists or radiology residents detect esophageal cancer on contrast-enhanced CT images.