Artificial Intelligence and Machine Learning in Perioperative Oncology: Advancing Precision Care
A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Artificial Intelligence in Medicine".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 73
Special Issue Editors
Interests: patient safety during anesthesia; the use of AI in postoperative recovery (PACU); optimization of anesthesia pharmacology through predictive analytics; enhancing perioperative workflows using AI-driven tools
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; natural language processing; predictive modeling; clinical research informatics; digital health; quality improvement; learning health system; translational science
Interests: artificial intelligence; machine learning; deep learning; patient safety; quality improvement; innovation; anesthesiology; critical care; digital health
Interests: artificial intelligence in clinical decision support; machine learning applications in perioperative care; predictive modeling for surgical outcomes; integration of AI into anesthesia monitoring
Special Issue Information
Dear Colleagues,
The integration of artificial intelligence (AI) and machine learning (ML) has the potential to revolutionize perioperative care for oncologic patients. By leveraging the power of data analysis and predictive modeling, these technologies can enhance decision-making, improve outcomes, and optimize the allocation of resources. This Special Issue aims to explore the innovative application of AI and ML in perioperative oncology, focusing on their impact on various aspects of patient care. The key areas of exploration include predictive modeling for risk stratification, developing AI-powered models to predict perioperative complications, identifying high-risk patients, and tailoring interventions accordingly; personalized treatment planning, utilizing AI and ML to optimize treatment plans based on individual patient characteristics, tumor biology, and perioperative factors; enhanced decision support systems, implementing AI-driven tools to assist clinicians in making informed decisions regarding anesthesia, surgical techniques, and postoperative management; robotic surgery and AI, Investigating the role of AI in enhancing the precision, efficiency, and outcomes of robotic-assisted surgical procedures; and natural language processing for clinical documentation, utilizing NLP to extract valuable information from electronic health records, facilitating data analysis, and improving clinical workflows. This Special Issue provides a platform for researchers to share their latest advancements in AI and ML applications for perioperative oncology. By highlighting the potential benefits and challenges associated with these technologies, we aim to drive further innovation and enhance the quality of care for oncologic patients.
Prof. Dr. Vijaya Gottumukkala
Dr. Hongfang Liu
Dr. Piyush Mathur
Guest Editors
Dr. Garry Brydges
Guest Editor Assistant
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Keywords
- artificial intelligence in healthcare
- machine learning in surgery
- deep learning, natural language processing
- computer vision in medical imaging, robotic process automation (RPA)
- digital twins in healthcare
- predictive analytics in healthcare
- augmented & virtual reality
- wearable technologies & IoT (Internet of Things)
- blockchain for secure medical data management
- edge computing in healthcare
- federated learning
- explainable AI (XAI)
- speech recognition and voice activated AI
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