AIMC Topic: Prostatic Neoplasms

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External validation of an artificial intelligence model for Gleason grading of prostate cancer on prostatectomy specimens.

BJU international
OBJECTIVES: To externally validate the performance of the DeepDx Prostate artificial intelligence (AI) algorithm (Deep Bio Inc., Seoul, South Korea) for Gleason grading on whole-mount prostate histopathology, considering potential variations observed...

Patient-specific deep learning for 3D protoacoustic image reconstruction and dose verification in proton therapy.

Medical physics
BACKGROUND: Protoacoustic (PA) imaging has the potential to provide real-time 3D dose verification of proton therapy. However, PA images are susceptible to severe distortion due to limited angle acquisition. Our previous studies showed the potential ...

Using multi-label ensemble CNN classifiers to mitigate labelling inconsistencies in patch-level Gleason grading.

PloS one
This paper presents a novel approach to enhance the accuracy of patch-level Gleason grading in prostate histopathology images, a critical task in the diagnosis and prognosis of prostate cancer. This study shows that the Gleason grading accuracy can b...

Artificial intelligence for detection of prostate cancer in biopsies during active surveillance.

BJU international
OBJECTIVES: To evaluate a cancer detecting artificial intelligence (AI) algorithm on serial biopsies in patients with prostate cancer on active surveillance (AS).

Prostate cancer risk assessment and avoidance of prostate biopsies using fully automatic deep learning in prostate MRI: comparison to PI-RADS and integration with clinical data in nomograms.

European radiology
OBJECTIVES: Risk calculators (RCs) improve patient selection for prostate biopsy with clinical/demographic information, recently with prostate MRI using the prostate imaging reporting and data system (PI-RADS). Fully-automated deep learning (DL) anal...

Mixed Supervision of Histopathology Improves Prostate Cancer Classification From MRI.

IEEE transactions on medical imaging
Non-invasive prostate cancer classification from MRI has the potential to revolutionize patient care by providing early detection of clinically significant disease, but has thus far shown limited positive predictive value. To address this, we present...

Prostate cancer diagnosis based on multi-parametric MRI, clinical and pathological factors using deep learning.

Scientific reports
Prostate cancer is one of the most common and fatal diseases among men, and its early diagnosis can have a significant impact on the treatment process and prevent mortality. Since it does not have apparent clinical symptoms in the early stages, it is...

Prostate MRI and artificial intelligence during active surveillance: should we jump on the bandwagon?

European radiology
OBJECTIVE: To review the components of past and present active surveillance (AS) protocols, provide an overview of the current studies employing artificial intelligence (AI) in AS of prostate cancer, discuss the current challenges of AI in AS, and of...

Integrated machine learning algorithms reveal a bone metastasis-related signature of circulating tumor cells in prostate cancer.

Scientific data
Bone metastasis is an essential factor affecting the prognosis of prostate cancer (PCa), and circulating tumor cells (CTCs) are closely related to distant tumor metastasis. Here, the protein-protein interaction (PPI) networks and Cytoscape applicatio...