Computerized medical imaging plays a pivotal role in cancer research, offering non-invasive methods to detect, diagnose, and monitor tumors. Techniques like MRI, CT scans, and PET scans provide detailed images of internal structures, aiding in early detection and precise localization of cancerous cells. Moreover, advancements in artificial intelligence empower these imaging modalities with enhanced accuracy and speed in analyzing vast amounts of data, leading to more effective treatment strategies. For instance, AI algorithms can identify subtle patterns indicative of cancer growth or metastasis, assisting clinicians in making timely and informed decisions. Integrating computerized imaging with molecular imaging techniques further refines cancer diagnosis by visualizing biological processes at the cellular level. As technology evolves, computerized medical imaging continues to revolutionize cancer research, offering hope for improved outcomes and personalized therapies.
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