From Abstracts to Action: How ASCOmind Streamlines Oncology Insights With Xiaoyan Wang, PhD; William Oh, MD; and Waqas Haque, MD, MPH

Tackling ASCO’s Information Overload

Each year, tens of thousands of oncologists convene at ASCO to absorb a plethora of presentations and abstracts. Dr. Wang explained the inspiration for ASCOmind: “Every year during ASCO, teams invest a huge amount of time and resources in staying on top of the flood of new data, and then after the meeting, spend another two or three months digesting everything. The question to me was, wouldn’t it be possible to have a system that can organize all the information in a digestible and structured format, not months later, but sooner—maybe even in real time?”

Designing ASCOmind

By building a multi‑agent system that preprocesses, categorizes, and analyzes abstracts, ASCOmind aims to provide structured, practice-relevant insights within days rather than months. The tool employs six different “agents,” each designed for a specific stage of analysis. Categorization, for example, draws on National Comprehensive Cancer Network (NCCN) guidelines to parse abstracts by cancer type and treatment pathways.

“We don’t just separate breast cancer from lung cancer,” explained Dr. Wang. “We go deeper—for example, differentiating relapsed/refractory multiple myeloma from newly diagnosed cases and linking trial data directly to practice.” The system’s architecture ensures that insights are organized in a clinically meaningful way rather than remaining a collection of isolated abstracts.

High-Risk Populations and Clinical Relevance

For practicing oncologists, the ability to differentiate by key subgroups is a major value proposition. “Cancer is increasingly divided into molecularly defined subsets. High‑risk population identification is critical—and AI may help us get to those insights faster,” noted Dr. Oh. By contextualizing data across trials, ASCOmind has the potential to highlight the patient groups most likely to benefit from specific therapies—an essential capability as oncology care becomes more personalized.

Accuracy, Reliability, and Real-World Use

Both speakers emphasized the importance of precision and reliability when integrating AI into research or practice. Dr. Wang explained that the development team evaluated ASCOmind using precision, recall, and F1 scores against gold‑standard oncology benchmarks. Dr. Oh added, “Reliability is everything. If we’re going to use these tools to influence patient care or clinical research, we need confidence that the outputs are both accurate and comprehensive.”

Implementation challenges—such as aligning with clinician workflows and maintaining explainability—remain, but both experts underscored that AI should complement, not replace, the human experience of conferences and collaboration.

Looking Ahead

The team sees future iterations of ASCOmind expanding beyond abstracts to include PubMed manuscripts, trial registries, and real-world evidence streams. Integration with conference platforms could make the tool a natural extension of how oncologists navigate meetings. “We want to map not just new data, but the entire oncology landscape, so that decisions are always made from the fullest possible picture,” concluded Dr. Wang.

Key Takeaways

• AI for efficiency: ASCOmind transforms months of manual review into structured insights within days.
• Clinically focused outputs: Multi‑agent design categorizes abstracts using established practice guidelines.
• Personalized oncology: Identifying high-risk subsets is a central feature.
• Reliability first: Accuracy, recall, and explainability must guide adoption.
• Future potential: Expansion to manuscripts, trial databases, and health news sources could broaden ASCOmind’s impact.

About the Speakers

Xiaoyan Wang, PhD, is a Research Professor at Tulane University and the Chief Scientist of IMO Health. Dr. Wang specializes in biomedical natural language processing and AI innovations for improving healthcare, and she has extensive experience in developing clinical evidence generation platforms in oncology, immunology, cardiovascular, and respiratory diseases.

William Oh, MD, a Professor of Internal Medicine in the Section of Medical Oncology and Hematology at Yale School of Medicine, where he is also the Director of Precision Medicine at Yale Cancer Center and Smilow Cancer Hospital. Dr. Oh specializes in genitourinary oncology, with decades of experience in caring for patients with prostate cancer. He is passionate about developing integrated oncology care teams and increasing the routine use of molecular and genetic testing for patients with cancer.

Waqas Haque, MD, MPH, is a second-year Hematology/Oncology Fellow at the University of Chicago. He recently completed his Internal Medicine Residency at New York University (NYU) in a Clinical Investigator Track. Dr. Haque has balanced his patient care work with a variety of research projects. During his fellowship training at the University of Chicago, he plans to further his work in innovative clinical trial design, value-based care delivery to cancer patients, and clinical investigation.