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Call for papers - Artificial intelligence in prostate cancer diagnostics

Guest Editors

Haoru Wang, MD, Children’s Hospital of Chongqing Medical University, China
Peng Xue, PhD, Chinese Academy of Medical Sciences and Peking Union Medical College, China
Ravishankar Jayadevappa, PhD, MS, University of Pennsylvania, USA
David-Dan Nguyen, MDCM, MPH, University of Toronto, Canada

Submission Status: Open   |   Submission Deadline: 20 January 2025

BMC Urology is calling for submissions to our Collection on Artificial intelligence and prostate cancer diagnostics. This Collection welcomes research delving into the innovative applications of artificial intelligence (AI) in prostate cancer diagnostics. Topics include the development and validation of AI algorithms, integration of AI-powered imaging techniques, prediction models for prognosis, AI-guided biopsy support, clinical implementation studies, and ethical considerations. We encourage contributions that advance our understanding of AI's role in revolutionizing prostate cancer care, aligning with our commitment to improving patient outcomes and quality of life.

New Content ItemThis Collection supports and amplifies research related to SDG 3: Good Health and Well-Being.

Meet the Guest Editors

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Haoru Wang, MD, Children’s Hospital of Chongqing Medical University, China

Dr Wang is a radiologist who focuses his research on the application of radiomics and deep learning based on medical imaging in differential diagnosis, prediction of the efficacy of neoadjuvant chemotherapy, risk stratification, and prognosis prediction of solid tumors. Additionally, he is interested in applying quantitative imaging parameters derived from functional magnetic resonance imaging and dual-energy computed tomography in solid tumors. Currently, he serves as an Editorial Board Member for BMC Medical Imaging.

Peng Xue, PhD, Chinese Academy of Medical Sciences and Peking Union Medical College, China

Dr Peng Xue is a postdoctoral fellow at the School of Population Medicine and Public Health, Chinese Academy of Medical Sciences, and Peking Union Medical College. His research interests focus on digital health, cancer prevention, and evidence-based medicine. His key focus is developing and validating new AI technologies and strategies that may improve health outcomes. He is the principal investigator for several National postdoctoral science-funded grants and an Editorial Board Member for several BMC and Nature family journals.

Ravishankar Jayadevappa, PhD, MS, University of Pennsylvania, USA

Dr Jayadevappa is a Research Associate Professor of Medicine (primary) and Associate Professor of Urology (secondary). He is also a Senior Fellow at the Leonard Davis Institute of Health Economics, a Fellow of the Institute on Aging, a Member of Abramson Cancer Center, and a co-director of the urology health services research program. His research focuses on analyzing the tradeoffs among economic efficiency, equity, and quality. Dr Jayadevappa’s health services research interests are health policies for the elderly, health outcomes, quality of life, health disparities, and comparative effectiveness of chronic diseases such as prostate cancer, bladder cancer, lung cancer, breast cancer, OAB, congestive heart failure, and Alzheimer’s disease-related dementias. His research underscores his commitment to advancing the understanding of and improving outcomes of patients with cancer using novel artificial intelligence (AI), machine learning, and patient-centered outcomes research.

David-Dan Nguyen, MDCM, MPH, University of Toronto, Canada

Dr David-Dan Nguyen is a urology resident at the University of Toronto, Canada. He is also a doctoral student at the Institute of Health Policy, Management, and Evaluation of the University of Toronto. His doctoral work will focus on population-based risk stratification of prostate cancer patients using machine learning. Dr David-Dan obtained his medical degree from McGill University, and his master’s in public health degree from the Harvard T.H. Chan School of Public Health. While pursuing his MPH degree, he was a research fellow at the Center for Surgery and Public Health, Brigham and Women’s Hospital, USA.

About the Collection

BMC Urology is inviting submissions to our Collection on the innovative intersection of Artificial Intelligence and prostate cancer diagnostics.

Prostate cancer (PCa) remains a significant health concern globally, with early and accurate diagnosis crucial for effective management and improved patient outcomes. Leveraging advancements in artificial intelligence (AI) and machine learning, researchers are revolutionizing prostate cancer diagnostics by developing intelligent algorithms capable of analyzing complex medical imaging data with unprecedented accuracy and efficiency. These AI-driven diagnostic tools hold immense promise in enhancing early detection rates, guiding personalized treatment strategies, and ultimately improving patient survival rates.

This Collection seeks to showcase cutting-edge research exploring the application of AI in prostate cancer diagnostics, including but not limited to:

  • Development and validation of AI algorithms for prostate cancer detection and risk stratification.
  • Multi-modal data integration of AI-powered imaging techniques in prostate cancer diagnosis. 
  • Prediction models utilizing AI for prognosis and treatment response assessment.
  • AI-guided biopsy guidance and targeting AI-powered clinical decision support systems (CDSS).
  • Clinical implementation and validation studies of AI-based diagnostic tools in real-world settings.
  • Ethical considerations and challenges in the deployment of AI-driven prostate cancer diagnostics.

By bringing together multidisciplinary expertise from the fields of urology, radiology, computer science, and biomedical engineering, this Collection aims to advance our understanding of how AI can revolutionize prostate cancer care, ultimately contributing to improved patient outcomes and quality of life.

This collection aligns with our commitment to supporting research that addresses Sustainable Development Goal 3: Good Health & Well-Being by fostering innovation in prostate cancer diagnostics and personalized medicine.

Image credit: © natali_mis /

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select Artificial intelligence in prostate cancer diagnostics from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.