- cardiac CT, MRI
- vascular CTA, MRA
- radiography
- thoracic and abdominal CT
- ultrasound
- DXA
Current
- imaging informatics
- workflow optimization
- artificial intelligence
- follow-up monitoring
- innovation & practice transformation
- patient-centered care
- clinical informatics
Previous
- radiation dose monitoring
- radiation dose reduction
- mobile apps for radiology education
Selected Publications
Jackson M Steinkamp, Charles Chambers, Darco Lalevic, Hanna M Zafar, Tessa S Cook: Toward Complete Structured Information Extraction from Radiology Reports Using Machine Learning. Journal of Digital Imaging 32(4): 554-564, Aug 2019.
CA Umscheid, Jonathan Wilen, Matthew Garin, JD Goldstein, TS Cook, Yulun Liu, Yong Chen, JS Myers: National Survey of Hospitalists' Experiences with Incidental Pulmonary Nodules. Journal of Hospital Medicine 46(6): 353-356, Jun 2019.
Langlotz CP, Allen B, Erickson BJ, Kalpathy-Cramer J, Bigelow K, Cook TS, Flanders AE, Lungren MP, Mendelson DS, Rudie JD, Wang G, Kandarpa K: A roadmap for foundational research on artificial intelligence in medical imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop. Radiology 291(3): 781-791, Jun 2019.
Liao GJ, Liao JM, Lalevic D, Zafar HM, Cook TS: Location, Location, Location: The Association Between Imaging Setting and Follow-Up of Findings of Indeterminate Malignant Potential. Journal of the American College of Radiology 16(6): 781-787, Jun 2019.
Martin-Carreras T, Cook TS, Kahn Jr CE: Readability of radiology reports: implications for patient-centered care. Clinical Imaging 54: 116-120, Mar 2019.
Cho JK, Zafar HM, Lalevic D, Cook TS: Patient Factor Disparities in Imaging Follow-Up Rates After Incidental Abdominal Findings. AJR 212(3): 589-595, Mar 2019.
Vey BL, Cook TS, Nagy P, Bruce RJ, Filice RW, Wang KC, Safdar NM: A Survey of Imaging Informatics Fellowships and Their Curricula: Current State Assessment. Journal of Digital Imaging 32(1): 91-96, Feb 2019.
George Shih, Carol C Wu, Safwan S Halabi, Marc D Kohli, Luciano M Prevedello, Tessa S Cook, Arjun Sharma, Judith K Amorosa, Veronica Arteaga, Maya Galperin-Aizenberg, Ritu R Gill, Myrna CB Godoy, Stephen Hobbs, Jean Jeudy, Archana Laroia, Palmi N Shah, Dharshan Vummidi, Kavitha Yaddanapudi, Anouk Stein: Augmenting the National Institutes of Health chest radiograph dataset with expert annotations of possible pneumonia. Radiology: Artificial Intelligence 1(1): e180041, Jan 2019.
Jeffrey D. Rudie, MD, PhD; Xie Long, PhD; Wang Jiancong; Jeffrey Duda, PhD; Joshua Choi, MD; Raghav Mattay, MD; Po-Hao Chen, MD, MBA; R Nick Bryan, MD, PhD; Emmanuel Botzolakis, MD, PhD; Ilya Nasrallah, MD, PhD; Tessa Cook, MD, PhD, CIIP; Suyash Mohan, MD; James Gee, PhD;
Andreas M. Rauschecker, MD, PhD: Deep Learning and Bayesian Inference System for Automated Brain MR Diagnosis Performs at Level of Academic Neuroradiologists and Augments Resident Performance. Society for Imaging Informatics in Medicine 2019 Notes: Oral presentation.
Andreas M. Rauschecker, MD, PhD; Long Xie, PhD; Wang Jiancong; Michael T. Duong; R. Nick Bryan, MD, PhD; Emmanuel Botzolakis, MD, PhD; Ilya Nasrallah, MD, PhD; Asha Kovalovich, MD; John Egan, MD; Tessa Cook, MD, PhD, CIIP; Suyash Mohan, MD; James Gee, PhD; Jeffrey D. Rudie, MD, PhD: Artificial Intelligence System Achieves Academic Neuroradiologist Level Diagnosis on Diseases of Cerebral Hemispheres. Society for Imaging Informatics in Medicine 2019 Notes: Oral presentation.
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Last updated: 05/06/2023
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