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Prostatic Neoplasms

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Assessing Algorithmic Fairness With a Multimodal Artificial Intelligence Model in Men of African and Non-African Origin on NRG Oncology Prostate Cancer Phase III Trials.

JCO clinical cancer informatics
PURPOSE: Artificial intelligence (AI) tools could improve clinical decision making or exacerbate inequities because of bias. African American (AA) men reportedly have a worse prognosis for prostate cancer (PCa) and are underrepresented in the develop...

PSMA PET/CT for prostate cancer diagnosis: current applications and future directions.

Journal of cancer research and clinical oncology
Prostate cancer (PCa) requires improved diagnostic strategies beyond conventional imaging. This review aimed to evaluate the role of prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) in diagnosing advan...

Evaluating prostate cancer diagnostic methods: The role and relevance of digital rectal examination in modern era.

Investigative and clinical urology
This review examines diagnostic methods for prostate cancer, focusing on the role of digital rectal examination (DRE) alongside modern advancements like prostate-specific antigen (PSA) testing, Prostate Health Index (PHI), magnetic resonance imaging ...

Effective reduction of unnecessary biopsies through a deep-learning-assisted aggressive prostate cancer detector.

Scientific reports
Despite being one of the most prevalent cancers, prostate cancer (PCa) shows a significantly high survival rate, provided there is timely detection and treatment. Currently, several screening and diagnostic tests are required to be carried out in ord...

Deep learning for quality assessment of axial T2-weighted prostate MRI: a tool to reduce unnecessary rescanning.

European radiology experimental
BACKGROUND: T2-weighted images are a critical component of prostate magnetic resonance imaging (MRI), and it would be useful to automatically assess image quality (IQ) on a patient-specific basis without radiologist oversight.

Feature selection for classification based on machine learning algorithms for prostate cancer.

Biomedical physics & engineering express
Microarray technology has transformed the biotechnological research to next level in the recent years. It provides the expression levels of various genes involved in a particular disease. Prostate cancer disease turned into life threatening cancer. T...

Identification of cancerous tissues based on residual neural network.

Scientific reports
The identification of cancerous tissues remains challenging due to the complexity of experimental methods and low identification accuracy rates. Therefore, this paper proposes a rapid identification method. We introduce a new theoretical transmission...

Enhanced hierarchical attention mechanism for mixed MIL in automatic Gleason grading and scoring.

Scientific reports
Segmenting histological images and analyzing relevant regions are crucial for supporting pathologists in diagnosing various diseases. In prostate cancer diagnosis, Gleason grading and scoring relies on the recognition of different patterns in tissue ...

Integrating multimodal imaging and peritumoral features for enhanced prostate cancer diagnosis: A machine learning approach.

PloS one
BACKGROUND: Prostate cancer is a common malignancy in men, and accurately distinguishing between benign and malignant nodules at an early stage is crucial for optimizing treatment. Multimodal imaging (such as ADC and T2) plays an important role in th...