AIMC Topic: Prostatic Neoplasms

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External Validation of an Artificial Intelligence Algorithm Using Biparametric MRI and Its Simulated Integration with Conventional PI-RADS for Prostate Cancer Detection.

Academic radiology
PURPOSE: Prostate imaging reporting and data systems (PI-RADS) experiences considerable variability in inter-reader performance. Artificial Intelligence (AI) algorithms were suggested to provide comparable performance to PI-RADS for assessing prostat...

[Making prostate cancer research accessible: chatGPT-4 as a tool to enhance lay communication].

Urologie (Heidelberg, Germany)
BACKGROUND AND OBJECTIVE: The abundant potential arising from various applications of artificial intelligence is gradually influencing academic and scientific communication. This study examines the suitability of ChatGPT‑4 for generating layperson's ...

Open-source deep-learning models for segmentation of normal structures for prostatic and gynecological high-dose-rate brachytherapy: Comparison of architectures.

Journal of applied clinical medical physics
BACKGROUND: The use of deep learning-based auto-contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containi...

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 ...

Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens.

Scientific reports
Prostate cancer (PCa) diagnosis faces significant challenges due to its complex pathological characteristics and insufficient pathologist resources. While deep learning-based image analysis (DLIA) shows promise in enhancing diagnostic accuracy, its a...

Proton dose calculation with transformer: Transforming spot map to dose.

Medical physics
BACKGROUND: Conventional proton dose calculation methods are either time- and resource-intensive, like Monte Carlo (MC) simulations, or they sacrifice accuracy, as seen with analytical methods. This trade-off between computational efficiency and accu...

Multichannel Contribution Aware Network for Prostate Cancer Grading in Histopathology Images.

Journal of computational biology : a journal of computational molecular cell biology
Gleason grading of prostate histopathology images is widely used by pathologists for diagnosis and prognosis. Spatial characteristics of cell and tissues through staining images is essential for accurate grading of prostate cancer. Although considera...

MRI-based radiomics for prediction of biochemical recurrence in prostate cancer: a systematic review and meta-analysis.

Abdominal radiology (New York)
BACKGROUND AND PURPOSE: Biochemical recurrence (BCR) following prostate cancer (PCa) treatment is a significant indicator of metastasis and mortality. Early prediction of BCR can guide treatment decisions, and optimize patient management strategies. ...

Deep learning techniques for proton dose prediction across multiple anatomical sites and variable beam configurations.

Physics in medicine and biology
To evaluate the impact of beam mask implementation and data aggregation on artificial intelligence-based dose prediction accuracy in proton therapy, with a focus on scenarios involving limited or highly heterogeneous datasets.In this study, 541 prost...