This year's PAS presenters who used Doctor T all demonstrate that modestly-resourced research teams can generate impressively upscaled results using Doctor T workflows and AI-based clinical NLP technology.

Abstract.	Authors
Prevalence of Osteoarthritic infection patients presenting with low inflammatory markers: a multi-center analysis	Nickolas Mancini, MD, MBA Sharon Smith, MD James Rudloff, MD Marvin Harper, MD Amir Kimia, MD	Session: Emergency Medicine 1 Works in Progress Friday, May 3, 2024 5:15 PM – 7:15 PM ET Nickolas Mancini,
Rate of bacteremia among children with skin abscesses that had a blood culture drawn	Elizabeth M. Waltman, BA Assaf Landschaft, Master of Science (M.Sc.) Jeffrey T. Neal, MD Eman Ansari, MD, MPH Al Ozonoff, PhD Amir Kimia, MD	Session: Emergency Medicine 4: Infections Saturday, May 4, 2024 3:30 PM – 6:00 PM ET Elizabeth M. Waltman
Discrepancy between expected skin abscess incision & drainage outcome and amount of pus expressed	Jeffrey T. Neal, MD Elizabeth M. Waltman, BA Eman Ansari, MD, MPH Eric Fleegler, MD MPH Al Ozonoff, PhD Assaf Landschaft, Master of Science (M.Sc.) Amir Kimia, MD	Session: Emergency Medicine 4: Infections Saturday, May 4, 2024 3:30 PM – 6:00 PM ET Jeffrey T. Neal, Harvard Medical School / Boston Children's Hospital,
Guidelines to standardize care for facial lacerations can improve racial inequities in plastic surgery repairs in the pediatric emergency department	David Mills, MD MPH Isabella G. Steidley, B.A. in Health and Human Biology Elizabeth M. Waltman, BA Todd W. Lyons, MD, MPH Andrew F. Miller, MD Amanda Stewart, MD, MPH Michael Monuteaux, ScD Ingrid Ganske, MD Chris A. Rees, MD, MPH Assaf Landschaft, Master of Science (M.Sc.) Amir Kimia, MD Eric Fleegler, MD MPH	Session: Health Equity/Social Determinants of Health 4 Saturday, May 4, 2024 3:30 PM – 6:00 PM ET David Mills,
Natural Language Processing-Assisted Evaluation of Empiric Antibiotics for Skin and Soft Tissue Infections	James Rudloff, MD Stephanie Fritz, MD, MSCI Albert M. Lai, PhD Amir Kimia, MD Rakesh D. Mistry, MD, MS Jason Newland, MD, MEd Fahd A. Ahmad, MD, MSCI	Session: Emergency Medicine 4: Infections Saturday, May 4, 2024 3:30 PM – 6:00 PM ET James Rudloff,
Enhancing surveillance of healthcare-associated violence using Natural Language Processing and clinical notes	Amir Kimia, MD Mark Waltzman, MD Kerri Ann A. Fournier, BSN, RN, CPN, CRN-BC Jennifer Welcher, MBA Carly E. Milliren, MPH Assaf Landschaft, Master of Science (M.Sc.) Al Ozonoff, PhD	Session: Quality Improvement/Patient Safety 2 Sunday, May 5, 2024 3:30 PM – 6:00 PM ET Amir Kimia,
Assessing Medical Large Language Models for Semantic Search in Pediatric Clinical Narratives	Assaf Landschaft, Master of Science (M.Sc.) Chase Parsons, DO, MBI Elizabeth M. Waltman, BA Amir Kimia, MD	Session: Technology 2 Sunday, May 5, 2024 3:30 PM – 6:00 PM ET Assaf Landschaft,
Use of Artificial Intelligence for lost-to-follow-up surveillance	Amir Kimia, MD Amy J. Starmer, MD, MPH Assaf Landschaft, Master of Science (M.Sc.) Phillip D. Hahn, MPH, CPH Andrea S. Bauer, MD Al Ozonoff, PhD Elizabeth M. Waltman, B.A. Kelly Fisher, MSN Dionne A. Graham, PhD	Session: Quality Improvement/Patient Safety 3 Monday, May 6, 2024 9:30 AM – 11:30 AM ET Amir Kimia

Doctor T (DR^T – Document Review Tool) is a graphic user interface for natural language processing (NLP)-assisted and NLP driven data review. DR^T was developed by pediatric emergency medicine physician, Dr. Amir Kimia MD, and a system architect computer scientist, Assaf Landschaft MSC.

DR^T software can be used by those individuals with little to no IT/computer science expertise. The software is user friendly and clinicians can leverage their training, insights, and experience to review the clinical notes provided by the data mining.

There was extensive time and energy put into which NLP modules are incorporated into DR^T to make it intuitive, and prone to less errors. As artificial intelligence tools continue to evolve, newer methodologies are ongoing along with updated versions. DR^T is not a commercial product or software. It has been used extensively by clinicians and quality improvement professionals at a pediatric hospital and a community hospital. If you are interested or have an idea to help improve patient care, the team that services and generates DR^T includes contractors, computer scientists and research assistants that are paid hourly, mainly through our funded collaborative projects.

For those interested in using DR^T for unfunded projects and cannot support the cost of installation and technical support/version updates, it is recommended to reach out to see if there is potential for collaboration. Our team is always open to new projects involving collaboration in federal and non-federal research grants. Alternatively, DR^T can be installed at your institution for a fee which includes a minimum number of hours for installation, technical support, software updates, and natural language processing basic rules and teaching.

DR^T workflow includes checks and balances, along with your medical ethics, to support a high standard of data analysis to help advance patient care. We have a high regard ensuring new users understand the AI and platform. We have a moral responsibility to make sure the data and science being used are sound. For questions please use the below contact information.

For example of some of our work, our recent publications grants and presentations appear on this website.

Contact:

Amir Kimia, MD

Associate Professor of Pediatrics, Harvard Medical School

Faculty Boston Children’s ED and Clinical Informatics Fellowship Program

Email: amir.kimia@childrens.harvard.edu

Phone: 617-355-6624