2nd Edition of International Cancer Research Conference
March 19-21, 2026 | Singapore
Role of AI in Cancer
Artificial intelligence (AI) is a term used to describe a computer that performs tasks that are similar to those performed by humans. AI integration in cancer care could enhance diagnosis accuracy and speed, aid clinical decision-making, and result in better health outcomes. Machine learning and other AI technologies can significantly improve the current mode of anticancer drug research. Clinical treatment driven by AI has the potential to make a significant difference in eliminating health inequities, especially in low-resource settings. Researchers can collaborate in real-time and share knowledge virtually utilising an AI-based system method, potentially healing millions. AI also has the potential to revolutionize oncology by leveraging big data to propel cancer care into the twenty-first century and beyond.
- Cancer drug development
- AI and Cancer Imaging
- AI and Translational Oncology
- Clinical decision making and AI
- AI Limitations and Future Directions
Rajvir Dahiya
University of California San Francisco, United States
Anyou Wang
DIFIBER LLC, United States
Michael Thompson
University of Toronto, Canada
Paulo Cesar De Morais
Catholic University of Brasilia, Brazil
Shilpa S Dhar
UT MD Anderson Cancer Center, United States
Eleni Petsalaki
University of Crete, Greece
Can Küçük
Dokuz Eylul University, TurkeySubmit your abstract Today
Title : A novel blood-based mRNA genomics technology for cancer diagnosis and treatment
Rajvir Dahiya, University of California San Francisco, United States
Title : Uncovering tumor-suppressive roles of histone modifiers in gastric cancer through spatial transcriptomics and epigenomics
Shilpa S Dhar, UT MD Anderson Cancer Center, United States
Title : Unveiling the synergism of radiofrequency therapy and graphene nanocomposite in tumor cell viability assay
Paulo Cesar De Morais, Catholic University of Brasilia, Brazil
Title : Analysis of the dynamic evolution and influencing factors of nutritional risk in breast cancer patients during treatment
Jingwen Yan, Sun Yat-sen University, China
Title : A case-based approach using IMPeTUs criteria in FDG PET/CT reporting of multiple myeloma
Mudalsha Ravina, All India Institute of Medical Sciences, India
Title : Updates on controversies surrounding the staging and management of newly diagnosed localized prostate cancer using prostate-specific membrane antigen (PSMA) positron emission tomography
Patricia Tai, University of Saskatchewan, Canada