The NLM Colloquia on Biomedical Data Science and Computational Biology Research is a regularly scheduled series of scientific lectures presented by the NLM Division of Intramural Research (DIR), a premier hub of innovation for computational biology and biomedical data science.
The NLM DIR invites experts from outside NLM to present at the Colloquia, where they can share their insights with research communities across NIH and worldwide in the rapidly evolving fields of biomedical data science and computational biology research, as well as how their work impacts these topic areas.
2026 NLM Colloquia Series
Opportunities for AI across the Pediatric TB Diagnostic Spectrum: A Clinician's Perspective
Event Date: Thursday, April 16, 2026
Time: 2:00pm–3:00pm
Speaker: Carlos M. Perez-Velez, MD
Location: The Lister Hill Center Auditorium (LHC, building 38A), and virtual via MS Teams
Abstract:
Tuberculosis (TB) in childhood remains a difficult infectious disease to diagnose because, in children with active disease—especially those with early non-severe disease—clinical manifestations are often nonspecific, radiologic abnormalities may be subtle, respiratory specimens are difficult to obtain, and the mycobacterial burden is often low, limiting the sensitivity of currently available microbiologic tests. Clinicians must therefore rely on multiple sources of evidence—clinical features, imaging, laboratory abnormalities, immunologic indicators, and exposure history—to guide treatment. These complexities make pediatric TB a valuable model for biomedical data science. Dr. Perez-Velez will discuss how AI may support clinicians across the pediatric TB diagnostic pathway, including recognizing findings suggestive of intrathoracic TB, estimating the likelihood that TB is the cause of disease, and assessing risk of progression to inform treatment decisions. He will emphasize AI’s potential to improve timely, clinically grounded decision-making when microbiologic confirmation is not possible. He will also highlight recent work in pediatric chest-radiography AI, illustrating both promise and limitations.
Speaker Bio:
Dr. Carlos M. Perez-Velez is an infectious diseases physician, hospital epidemiologist, and academic clinician whose work spans pediatric and adult tuberculosis, healthcare epidemiology, infection prevention and control, respiratory infectious diseases, and global health. He serves as Hospital Epidemiologist and Medical Director of the Infection Prevention and Control Program at the Raymond G. Murphy VA Medical Center in Albuquerque, New Mexico, and is Associate Professor of Clinical Medicine at both the University of New Mexico and the University of Arizona.
Dr. Perez-Velez is internationally recognized for his work in pediatric and drug-resistant tuberculosis, particularly in the development of innovative specimen-collection methods, radiologic approaches, and artificial intelligence tools for diagnosis in children. He is Principal Investigator of an NIH-supported study developing AI-based methods for detection of pediatric tuberculosis on chest radiographs. He has published extensively in leading journals, including The New England Journal of Medicine, The Lancet, and JAMA Pediatrics, and has served as an invited speaker and consultant for NIH, WHO, CDC, and international tuberculosis networks.
How to Join:
Location: The Lister Hill Center Auditorium (LHC, Building 38A)
This talk will also be broadcast live: MS Teams
Interpreting services are available upon request. Individuals with disabilities who need reasonable accommodation to participate in this lecture should contact NLMColloquia@nih.gov or the Federal Relay (1-800-877-8339).
Questions during the presentation can be sent to: NLMColloquia@nih.gov.
Sponsored by:
Richard Scheuermann, PhD
Scientific Director, Division of Intramural Research, National Library of Medicine