close
close
gmask

Artificial Intelligence-Assisted Radiotherapy in Pelvic and Abdominal Malignancies

Irishu

The integration of artificial intelligence (AI) in radiotherapy of pelvic and abdominal malignancies represents a transformative advance in oncology. The ability of AI to increase precision in treatment planning, optimize radiation dose, and predict treatment outcomes holds great promise for improving patient care. This special issue explores the potential of AI-assisted radiotherapy in the management of malignancies such as cervical, ovarian, colorectal, and prostate cancers.

Contributions are invited from experts in medical physics, radiation oncology, computer science, and related fields who are at the forefront of integrating AI into clinical practice. Researchers from academic institutions, cancer centers, and industry leaders who are developing AI tools for oncology are encouraged to share their findings and insights. We particularly welcome studies that address the clinical application, challenges, and future directions of AI in radiotherapy for pelvic and abdominal tumors.

The main objective of this special issue is to explore the transformative role of AI in improving the precision, efficacy and outcomes of radiotherapy for pelvic and abdominal malignancies. By bringing together cutting-edge research, clinical experience and technological advances, this issue aims to provide a comprehensive overview of the impact of AI on treatment planning, adaptive radiotherapy and patient management. We aim to highlight innovative applications of AI in improving radiation targeting, reducing treatment toxicity and enabling personalized care for cancers such as cervix, ovarian, colorectal and prostate. Furthermore, the issue will address current challenges, ethical considerations and future directions, aiming to promote collaboration and inspire further research in AI-enabled oncology.

We welcome submissions of original research, methods, reviews, mini-reviews, perspectives, clinical trials, and short research reports. Specific potential areas of clinical research include, but are not limited to:
• Artificial Intelligence in Treatment Planning: Innovations in AI-enabled algorithms to increase treatment precision, including contouring, dose optimization, and adaptive radiotherapy.
• Artificial Intelligence in Image Guided Radiotherapy (IGRT): Applications of artificial intelligence in improving imaging techniques, target localization, and real-time treatment adjustments.
• Predictive Analytics and Outcome Prediction: Using artificial intelligence to predict patient outcomes, treatment responses, and potential side effects, with a focus on personalized treatment strategies.
• Clinical Application and Case Studies: Real-world examples and studies on the integration of AI into clinical practice, including workflow optimization and interdisciplinary collaboration.
• Ethical Issues and Regulatory Challenges: Addressing the ethical, legal, and regulatory aspects of AI in oncology and precision medicine, particularly in patient data management and decision-making.
• Future Directions and Emerging Technologies: Exploring future developments in artificial intelligence that could revolutionize radiotherapy, such as machine learning, deep learning and big data analytics.


Keywords: Radiotherapy, Artificial Intelligence, Reproductive System, Digestive System, Malignant Tumors


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 statement. Frontiers reserves the right to direct an out-of-scope manuscript to a more appropriate section or journal at any stage of peer review.

The integration of artificial intelligence (AI) in radiotherapy of pelvic and abdominal malignancies represents a transformative advance in oncology. The ability of AI to increase precision in treatment planning, optimize radiation dose, and predict treatment outcomes holds great promise for improving patient care. This special issue explores the potential of AI-assisted radiotherapy in the management of malignancies such as cervical, ovarian, colorectal, and prostate cancers.

Contributions are invited from experts in medical physics, radiation oncology, computer science, and related fields who are at the forefront of integrating AI into clinical practice. Researchers from academic institutions, cancer centers, and industry leaders who are developing AI tools for oncology are encouraged to share their findings and insights. We particularly welcome studies that address the clinical application, challenges, and future directions of AI in radiotherapy for pelvic and abdominal tumors.

The main objective of this special issue is to explore the transformative role of AI in improving the precision, efficacy and outcomes of radiotherapy for pelvic and abdominal malignancies. By bringing together cutting-edge research, clinical experience and technological advances, this issue aims to provide a comprehensive overview of the impact of AI on treatment planning, adaptive radiotherapy and patient management. We aim to highlight innovative applications of AI in improving radiation targeting, reducing treatment toxicity and enabling personalized care for cancers such as cervix, ovarian, colorectal and prostate. Furthermore, the issue will address current challenges, ethical considerations and future directions, aiming to promote collaboration and inspire further research in AI-enabled oncology.

We welcome submissions of original research, methods, reviews, mini-reviews, perspectives, clinical trials, and short research reports. Specific potential areas of clinical research include, but are not limited to:
• Artificial Intelligence in Treatment Planning: Innovations in AI-enabled algorithms to increase treatment precision, including contouring, dose optimization, and adaptive radiotherapy.
• Artificial Intelligence in Image Guided Radiotherapy (IGRT): Applications of artificial intelligence in improving imaging techniques, target localization, and real-time treatment adjustments.
• Predictive Analytics and Outcome Prediction: Using artificial intelligence to predict patient outcomes, treatment responses, and potential side effects, with a focus on personalized treatment strategies.
• Clinical Application and Case Studies: Real-world examples and studies on the integration of AI into clinical practice, including workflow optimization and interdisciplinary collaboration.
• Ethical Issues and Regulatory Challenges: Addressing the ethical, legal, and regulatory aspects of AI in oncology and precision medicine, particularly in patient data management and decision-making.
• Future Directions and Emerging Technologies: Exploring future developments in artificial intelligence that could revolutionize radiotherapy, such as machine learning, deep learning and big data analytics.


Keywords: Radiotherapy, Artificial Intelligence, Reproductive System, Digestive System, Malignant Tumors


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 statement. Frontiers reserves the right to direct an out-of-scope manuscript to a more appropriate section or journal at any stage of peer review.