AI Medical Compendium Topic:
Prostatic Neoplasms

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Anatomical dimensions using preoperative magnetic resonance imaging: impact on the learning curve of robot-assisted laparoscopic prostatectomy.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVE: To evaluate the impact of anatomical dimensions as measured using preoperative magnetic resonance imaging on the outcomes of robot-assisted laparoscopic prostatectomy.

A data-driven approach to prostate cancer detection from dynamic contrast enhanced MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Magnetic resonance imaging (MRI), particularly dynamic contrast enhanced (DCE) imaging, has shown great potential in prostate cancer diagnosis and staging. In the current practice of DCE-MRI, diagnosis is based on quantitative parameters extracted fr...

A systematic review of AI as a digital twin for prostate cancer care.

Computer methods and programs in biomedicine
Artificial Intelligence (AI) and Digital Twin (DT) technologies are rapidly transforming healthcare, offering the potential for personalized, accurate, and efficient medical care. This systematic review focuses on the intersection of AI-based digital...

A deployment safety case for AI-assisted prostate cancer diagnosis.

Computers in biology and medicine
Deep learning (DL) has the potential to deliver significant clinical benefits. In recent years, an increasing number of DL-based systems have been approved by the relevant regulators, e.g. FDA. Although obtaining regulatory approvals is a prerequisit...

Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Diagnosis codes documented in electronic health records (EHR) are often relied upon to clinically phenotype patients for biomedical research. However, these diagnoses can be incomplete and inaccurate, leading to false negatives when search...

Bridging the gap: Evaluating ChatGPT-generated, personalized, patient-centered prostate biopsy reports.

American journal of clinical pathology
OBJECTIVE: The highly specialized language used in prostate biopsy pathology reports coupled with low rates of health literacy leave some patients unable to comprehend their medical information. Patients' use of online search engines can lead to misi...

Machine Learning and Urinary Incontinence in Prostate Cancer: A Generalized Additive Model of Physical Activity and Recovery Patterns.

Studies in health technology and informatics
The ASCAPE project aims to improve the health-related quality of life of prostate cancer patients using artificial intelligence-driven solutions. This study tries to unravel the complex relationships between patient data variables and urinary inconti...

Deep Learning-based Anatomy-Aware Morph Model for Registration of Prostate Whole-Mount Histopathology to MRI.

Radiology. Imaging cancer
Purpose To develop and evaluate a novel deep learning-based approach for registering presurgical MR and whole-mount histopathology (WMHP) images of the prostate. Materials and Methods This retrospective study included patients who underwent prostate ...