About this Research Topic
Genitourinary (GU) cancers remain a challenge as one of the most common malignancies worldwide. Although there have been great strides towards the detection, diagnosis, and therapeutic approaches of GU cancers, the impact and role of artificial intelligence (AI) are yet to be explored. AI has enabled significant development and efficiency towards improving and providing further support in healthcare. AI tools are primarily utilized to enhance the accuracy of histopathology assessment, tumor detection, diagnostic imaging, risk stratification, and personalized treatment for patients. There have indeed been myths surrounding AI in medicine in the earlier days. However, with advancements in computational power, significant achievements have been made in the last twenty years, in which some have been actually transformed into clinically useful platforms.
This Research Topic aims to explore the impact and role of AI in genitourinary oncology, including the scopes of complex medical data analysis to obtain unrecognized insight, analysis and interpretation of imaging and pathological data, and data monitoring and pattern recognition. We will focus on how AI can be utilized to better achieve the goals in GU oncology and improve patient care by being used in the correct direction, rather than answering the simple question, “Who or which does it better.”
Topics of interest are but not limited to:
- Estimating prognosis and survival of patients
- Digital pathology interpretation
- Radiology interpretation
- How AI impacts the efficiencies of practice and patient care
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases that are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of the scope of this section and will not be accepted as part of this Research Topic.
This Research Topic aims to explore the impact and role of AI in genitourinary oncology, including the scopes of complex medical data analysis to obtain unrecognized insight, analysis and interpretation of imaging and pathological data, and data monitoring and pattern recognition. We will focus on how AI can be utilized to better achieve the goals in GU oncology and improve patient care by being used in the correct direction, rather than answering the simple question, “Who or which does it better.”
Topics of interest are but not limited to:
- Estimating prognosis and survival of patients
- Digital pathology interpretation
- Radiology interpretation
- How AI impacts the efficiencies of practice and patient care
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases that are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of the scope of this section and will not be accepted as part of this Research Topic.
Keywords: artificial intelligence, bladder, genitourinary, kidney, oncology, prostate, urothelial
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
