2nd Edition of International Cancer & Immuno-Oncology Conference
March 19-21, 2026 | Singapore
Role of Artificial Intelligence in Cancer Diagnostics
The role of artificial intelligence (AI) in cancer diagnostics is expanding rapidly, with AI systems now capable of analyzing medical images, genomic data, and patient histories to assist in the early detection of cancer. AI-powered tools can analyze radiological images such as CT scans, MRIs, and mammograms to identify abnormalities with greater accuracy than traditional methods. By integrating patient data with machine learning algorithms, AI can predict cancer risks, identify potential biomarkers, and suggest optimal treatment plans. Furthermore, AI is helping pathologists interpret biopsy results more quickly and accurately, leading to faster diagnoses. The integration of AI into cancer diagnostics not only improves the speed and accuracy of detection but also enhances the overall quality of care, paving the way for more personalized and effective treatment options.
Rajvir Dahiya
University of California San Francisco, United States
Atif A Ahmed
University of Washington-Seattle Children’s Hospital, United States
Anyou Wang
DIFIBER LLC, United States
Paulo Cesar De Morais
Catholic University of Brasilia, Brazil
Allen Chen
Olympic Medical Center, United States
Shilpa S Dhar
UT MD Anderson Cancer Center, United States
Ritu Khanna
University of Manchester, United KingdomSubmit 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 : tRNA-derived fragment 3′tRF-AlaAGC modulates cell chemoresistance and M2 macrophage polarization via binding to TRADD in breast cancer
Feng Yan, The Affiliated Cancer Hospital of Nanjing Medical University, China
Title : Integrating single-cell and spatial transcriptomics to uncover and elucidate GP73-mediated pro-angiogenic regulatory networks in hepatocellular carcinoma
Jiazhou Ye, Guangxi Medical University Cancer Hospital, China
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 : Integrative multi-omics reveals metabolic–stemness coupling and novel therapeutic targets in osteosarcoma chemoresistance
Jinyan Feng, Tianjin Medical University Cancer Institute and Hospital, China