SUMMARY
Irbaz B. Riaz, M.B.B.S., M.S., specializes in managing genitourinary cancers, including prostate, kidney, bladder and testicular cancers. Dr. Riaz also holds a doctorate in clinical and translational science and a master's degree in biomedical informatics. With profound expertise in clinical informatics and data science, Dr. Riaz integrates cutting-edge quantitative research methods, large-scale observational data analysis, computational biology and machine learning into his practice to enhance patient care.
Dr. Riaz leads artificial intelligence (AI) cancer research at Mayo Clinic, where his research is at the forefront of AI in healthcare and clinical computational oncology. His work encompasses various AI methodologies, including natural language processing for mining clinical data, predictive modeling, genomic data analysis, and computer vision for digital pathology and medical imaging. Dr. Riaz and his team pioneer new AI techniques, explore biases in AI applications and advance bioinformatics.
Dr. Riaz's current projects focus on leveraging large language models for clinical practice and discovery, developing AI-supported living clinical practice guidelines, and integrating multimodal data to enhance early cancer detection and predict clinical outcomes. The overarching goal is to harness AI and genomics to unveil novel insights, enhance patient outcomes and reduce treatment burdens through improved patient communication and education.
Dr. Riaz is committed to promoting a vision of fair, equitable and safe AI-assisted patient care that will transform the landscape of treating and managing patients.
Focus areas
- Personalize treatment recommendations using AI to ensure each patient receives the most effective therapy.
- Develop AI-enhanced cancer registries to foster precision medicine.
- Use data-driven approaches for patient care optimization.
- Match patients to clinical trials more effectively and reduce enrollment disparities.
- Implement living clinical practice guidelines that evolve with emerging data.
- Enhance patient communication to reduce wait times and improve care experiences.
Significance to patient care
Dr. Riaz uses advanced technology to develop new drugs, improve clinical trials, and better understand and treat cancer. He works with AI, which helps analyze a lot of information quickly and accurately. This includes everything from a patient's medical images to genetic information, helping the healthcare team spot cancer earlier and understand it better.
By using AI, Dr. Riaz aims to find the most effective treatments for each patient. This means patients get the care that's best suited for them, potentially with fewer side effects. The goal is to make treatments more effective and less burdensome by making communication clearer and reducing waiting times. This approach helps address needs that current treatments do not fully meet, improving patient care overall.
Professional highlights
- American Society of Clinical Oncology:
- Career Development Award, 2023-present.
- Lead, Living Guidelines Working Group, 2023-present.
- Conquer Cancer Merit Award, every year 2017-2023.
- Director, Living Evidence Program, Evidence-Based Practice Center, Mayo Clinic, 2023-present.
- Grant, Seed Grant Program, Mayo Clinic and Arizona State University Alliance for Health Care, 2023-present.
- Lead, Artificial Intelligence Working Group, National Comprehensive Cancer Network, 2023-present.
- T32 Award, Biomedical Informatics and Data Science, National Library of Medicine, 2021-2023.
- Endeavor Award, Government of Australia, 2010-2012.