About this Research Topic
Despite continued research and innovation, breast and gynecological cancers still present a significant public health challenge worldwide, with millions of new cases and deaths annually. Early diagnosis and targeted intervention are vital to improving survivorship, and recent advances have brought forward several novel diagnostic and treatment options. These include personalized gene therapies, Artificial Intelligence (AI) screening, and other digital technologies. By implementing AI in cancer care, these tools can detect cancer, aid in decision-making, and recommend treatment approaches.
This Research Topic aims to explore the potential and challenges of integrating AI and new technologies in the detection, diagnosis, and treatment of breast and gynecological cancers. Critical to this exploration is understanding how AI can enhance early diagnosis, the role of AI in modeling and predicting treatment outcomes, and how these technologies can be harnessed to deliver personalized care. Additionally, considering the capacity of AI and digital health technologies to improve accessibility (particularly in resource-limited settings) is important to comprehensively analyse their impact on current and future cancer care.
This Research Topic welcomes the submission of original research, brief research reports, clinical trials, systematic reviews, reviews, mini-reviews, and perspective articles addressing, but not limited to, the following themes:
• AI applications in breast and gynecological cancer screening and detection, including advances in imaging and accessibility.
• AI applications in radiation oncology and therapeutic planning for breast and gynecological cancers.
• Telemedicine and digital health tools for breast and gynecological cancer care, including survivorship care and rural or resource-limited settings.
• AI-driven predictions and models of therapy effectiveness and recurrence risk for breast and gynecological cancer management.
• Big Data and AI innovations in early breast and gynecological cancer detection and survival analysis.
• AI's emerging role in drug development, precision therapy, and other aspects of breast and gynecological cancer research.
• Economic analysis of implementing technological advancements in the screening, diagnosis, and treatment of breast and gynecological cancers.
By exploring these areas, we can harness the power of new technologies and AI to make significant strides in the fight against breast and gynecological cancer.
Jesus Garcia-Donas has advisory roles with, and has received honoraria, research funding and other expense payments from, Bristol Meiers, Bayer, Astellas, Ipsen, Astra Zeneca, Merck, MSD, Gilead, Novartis, GSK, Lilly, Health in code, Thermofisher, Illumina, Pharmamar, Roche, Pfizer,Janssen, and Piere Fabre. All other Research Topic Editors declare no conflicts of interest.
This Research Topic aims to explore the potential and challenges of integrating AI and new technologies in the detection, diagnosis, and treatment of breast and gynecological cancers. Critical to this exploration is understanding how AI can enhance early diagnosis, the role of AI in modeling and predicting treatment outcomes, and how these technologies can be harnessed to deliver personalized care. Additionally, considering the capacity of AI and digital health technologies to improve accessibility (particularly in resource-limited settings) is important to comprehensively analyse their impact on current and future cancer care.
This Research Topic welcomes the submission of original research, brief research reports, clinical trials, systematic reviews, reviews, mini-reviews, and perspective articles addressing, but not limited to, the following themes:
• AI applications in breast and gynecological cancer screening and detection, including advances in imaging and accessibility.
• AI applications in radiation oncology and therapeutic planning for breast and gynecological cancers.
• Telemedicine and digital health tools for breast and gynecological cancer care, including survivorship care and rural or resource-limited settings.
• AI-driven predictions and models of therapy effectiveness and recurrence risk for breast and gynecological cancer management.
• Big Data and AI innovations in early breast and gynecological cancer detection and survival analysis.
• AI's emerging role in drug development, precision therapy, and other aspects of breast and gynecological cancer research.
• Economic analysis of implementing technological advancements in the screening, diagnosis, and treatment of breast and gynecological cancers.
By exploring these areas, we can harness the power of new technologies and AI to make significant strides in the fight against breast and gynecological cancer.
Jesus Garcia-Donas has advisory roles with, and has received honoraria, research funding and other expense payments from, Bristol Meiers, Bayer, Astellas, Ipsen, Astra Zeneca, Merck, MSD, Gilead, Novartis, GSK, Lilly, Health in code, Thermofisher, Illumina, Pharmamar, Roche, Pfizer,Janssen, and Piere Fabre. All other Research Topic Editors declare no conflicts of interest.
Keywords: artificial intelligence, machine learning, new technologies, breast cancer, gynecological cancer, cervical cancer, screening, precision medicine
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.
