"10 Years of Cancer Informatics"

The 20th Cancer Informatics for Cancer Centers Symposium highlights a landmark event

"A Decade of Cancer Informatics" 

Come help us define the next ten years together

Cancer Researchers and care providers have faced an overwhelming volume of data from a multitude of sources. Data formats, consistent use of standards, and idiosyncratic tools and systems have limited our ability as data scientists and informaticians to scale our work and “learn from every patient.” 

AI promises to transform oncology research and care. Large language models like ChatGPT have clear applications from helping respond to patient inquiries, matching patients to clinical trials, to assessing treatment, outcomes, and quality of life. Implementing AI methods will need clear practices and standards for evaluation and validation. Factors like patient privacy need to be incorporated. None-the-less, it is clear that AI is already transforming imaging, lab data, and clinical data in cancer research and care. These issues infused our discussions at our summer 2022 Informatics in Radiation Oncology Symposium as they will infuse all our events for the foreseeable future. These are exciting times for informatics, data science, and oncology.

Over the past decade projects that integrate -omics, lab and clinical data have made it clear that standards for data entry, deep annotation, advanced analytics, and query engines drive innovation and adoption.  Cancer research information exchange is now core to cancer research and care. Sources of data include electronic health records, lab systems, image repositories, disease registries, and clinical trial systems, with varying degrees of completeness, quality, and research utility.  Computational methods to evaluate risk, improve early detection of cancer, develop novel cancer interception methods, improve the effectiveness of therapies, and improve outcomes for cancer survivors all require well-designed experiments and well-defined data. 

 
During the past ten years of Ci4CC we have highlighted as a community many of the data-driven advances in cancer research and care.  Health disparities and data science are interconnected in various ways.  Data Science plays a crucial role in identifying health disparities, which are the differences in health outcomes between different populations.  We will highlight how Data science techniques allow researchers and healthcare professionals to analyze large datasets and identify patterns or trends related to health equities.

As we look forward to the next ten years, we believe that data and computation and therefore AI,  informatics and data science will be key drivers of innovation in cancer. And we look to all of you to prognosticate on what the next advances should be and what the impact of those advances can or needs to be.

Sessions

• Artificial Intelligence in Oncology
• Learning Health Systems and Oncology Research
• Real World Evidence, Continuous Monitoring
• Synthetic Arms for Clinical Trials
• New Topics in Precision Oncology
• Data Platforms, Data Sharing, Data Commons
• Role of Informatics in Health Equity
• Data Science and Informatics as Cancer Center CCSG Programs

Round Table Open Topics

• Large Language Models across Oncology
• EMR's and Research
• Emerging Technologies and Society Innovation Hub
• Genomics, Spatial -omics, Imaging, microenvironment
• Quantitative Science Workforce
• Fairness and Equity in AI
• Oncology Foundations & Cancer Society Networks
• Cancer Center Shared Resources
• CCSG Informatics & Research IT
• Grant Opportunities in Cancer Informatics
• Precision Pathways and Value Based Care

Anniversary Symposium Chairs

Program Committee, Keynotes, & Session Chairs