The National Academy of Medicine (探花app) has selected 10 individuals for the 2026 class of the 探花app Scholars in Diagnostic Excellence program. This collaborative program in partnership with the Council of Medical Specialty Societies (CMSS) offers a one-year, part-time experience for exceptional health professionals to advance their diagnostic skills, make significant contributions to improve clinical diagnosis at the national level, and accelerate their career development as national leaders in the field.
The scholars were chosen based on their professional qualifications and accomplishments, demonstrated leadership in the field, and potential to advance diagnostic excellence. They were also chosen based on the quality and feasibility of their program proposals to improve diagnosis and reduce diagnostic errors at the national level, building upon the work of the National Academies of Sciences, Engineering, and Medicine鈥檚 2015 consensus report .
鈥淒iagnostic excellence is essential to improving the quality, safety, and accessibility of health care,鈥 said National Academy of Medicine President Victor J. Dzau. 鈥淲e are proud to welcome this outstanding class of scholars, whose innovative work will help reduce diagnostic errors and improve outcomes for patients and families nationwide.鈥
The 2026 探花app Scholars in Diagnostic Excellence and their program proposals are:
- Dania Daye, MD, PhD, associate professor of radiology; vice chair of practice transformation; director, Center of High Value Imaging, Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis.
鈥淢ulti-Agentic AI System for End-to-End Management of Incidental Findings in Diagnostic Imaging鈥
- Ahmed Hassoon, MD, MPH, assistant research professor, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Department of Neurology, Johns Hopkins Medicine, Department of Computer Science, Johns Hopkins Whiting School of Engineering, Baltimore
鈥淭he Patient Advocate to Empowering Patients in the Diagnostic Process: A Safety Framework and Modus Operandi for Agentic AI-Mediated Error Interception鈥
- Shuhan He, MD, emergency physician and clinical informatician, Department of Emergency Medicine, Massachusetts General Hospital, Boston
鈥淒iagnostic Safety by Design: Clinician-Centered Redesign and Multi-Site Deployment of a Digital Uncertainty-Reduction Tool for Emergency Medicine鈥
- Julius Oatts, MD, MHS, attending physician and associate professor, Department of Ophthalmology, Children鈥檚 Hospital of Philadelphia / University of Pennsylvania Perelman School of Medicine, Philadelphia
鈥淚mproving Retinopathy of Prematurity Diagnostic Verification and Predictive Modeling Using a Novel Image Grading Score鈥
- Andrei S. Purysko, MD, FSAR, section head, Abdominal Imaging, Diagnostics Institute, Cleveland Clinic, Cleveland, OH; associate professor of radiology, Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland
鈥淚mproving Prostate Cancer Diagnosis Through Standardized Prostate MRI Image Quality Assessment鈥
- Adam Rodman, MD, MPH, director or AI programs, Carl J Shapiro Institute for Research and Education, Beth Israel Deaconess Medical Center, Boston
鈥淟aying the Groundwork for an Effective, Evidence-Grounded LLM-Based Second Opinion Trigger System for High-Risk Hospitalized Inpatients鈥
- Cory Rohlfsen, MD, associate professor, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, Neb.
鈥淐an Diagnostic Excellence Be Measured?鈥
- Lucy Schulson, MD, MPH, assistant professor, Boston University Chobanian & Avedisian School of Medicine; attending physician, Section of General Internal Medicine, Boston Medical Center physician, Immigrant and Refugee Health Center, Boston
鈥淏ridging Diagnostic Gaps: Using AI to Identify Missed Heart Failure with Preserved Ejection Fraction Diagnosis to Improve Diagnostic Equity in Ambulatory Care鈥
- Kathleen E. Walsh, MD, MSc, director, healthcare quality and safety research program; director, Harvard-wide pediatric health services research fellowship, Division of General Pediatrics, Boston Children鈥檚 Hospital, Boston
鈥淚mproving Communication of Pediatric Diagnostic Uncertainty with Outpatient Families鈥
- Yize Zhao, PhD, associate professor, Department of Biostatistics, Yale School of Public Health, New Haven, Conn.
鈥淒ynamic Diagnostic Surveillance: An Equity-Centered, Uncertainty-Aware Framework for Timely ADRD Diagnosis from EHRs鈥
“I am excited to work with this exceptional cohort of scholars dedicated to diagnostic excellence across specialties and disciplines,” said Helen Burstin, chief executive officer of the Council of Medical Specialty Societies. “Through our strategic partnership with the 探花app, we’re building a powerful network of leaders who are transforming health care through groundbreaking improvements in the use of AI and diagnostic excellence.”
The scholars will continue in their primary posts while engaging part time over a one-year period in developing an implementation plan for their proposals, as well as participating in monthly educational sessions, cohort learning activities, and professional networking opportunities through the 探花app and CMSS. In addition, each scholar will be matched with a mentor or mentors who can provide professional guidance and subject matter or technical expertise for their work. A flexible research grant will be awarded to every scholar.
Funding for the program is provided by the Gordon and Betty Moore Foundation, with additional support from the Coordinating Center for Diagnostic Excellence (CODEX) at the University of California, San Francisco.
