Paulo Eduardo de Aguiar Kuriki, M.D. Titles and Appointments Assistant Professor Schools Medical School Departments Radiology You have reached the Academic Profile. For more information on the doctor and patient care, please visit the clinical profile. Biography Paulo E. A. Kuriki, M.D., is an Assistant Professor of Radiology at UT Southwestern Medical Center, a member of its Neuroradiology & Intervention Division, and Director of the Artificial Intelligence in Radiology Hub (AIR-Hub). He leads the development and clinical implementation of artificial intelligence technologies in radiology, with a focus on translating advances in AI into safe, scalable systems used in everyday clinical practice. At UT Southwestern, Dr. Kuriki leads a multidisciplinary team that develops, validates, deploys, and monitors AI-enabled clinical applications. The AIR-Hub has developed and integrated into Epic an automated imaging protocol platform that processes more than 20,000 imaging protocols per month. His team has also developed an AI-assisted radiology reporting platform used by more than 150 radiologists and trainees and supporting more than 20,000 radiology reports per month. Evaluation in CT and MRI reports demonstrated a greater than 10% reduction in reading time, along with improvements in report quality and reduced cognitive burden for radiologists. His work emphasizes physician adoption, workflow integration, reliability, safety, and measurable clinical and operational impact. Dr. Kuriki also leads the development of next-generation clinical AI systems, including large language models, vision-language models, multimodal foundation models, and agentic AI. His team is developing models that combine medical imaging and clinical information to support automated radiology report generation and other complex clinical tasks. The AIR-Hub is currently evaluating internally developed vision-language models for chest and spine report drafting in real-world radiology workflows. His work also extends to medical education, quality improvement, and AI governance. His team developed RADAR, a platform that analyzes differences between residents' preliminary reports and attending physicians' final reports to provide scalable feedback and identify meaningful learning opportunities. The AIR-Hub also develops infrastructure for AI performance monitoring, clinical safety, and post-deployment evaluation. Originally from São Paulo, Brazil, Dr. Kuriki received his medical degree, completed his radiology residency training, and pursued a neuroradiology clinical fellowship at Universidade Federal de São Paulo. He later completed an Advanced Neuroradiology Fellowship at UT Southwestern. Before joining the UT Southwestern faculty, Dr. Kuriki practiced as a neuroradiologist and served as Head of Artificial Intelligence in Diagnostic Operations at DASA, one of Brazil's largest diagnostic companies, where he led AI deployment across large-scale diagnostic imaging operations. His work included an MRI denoising solution that reduced acquisition time by approximately 30%, natural language processing systems for identifying actionable findings, and workflow automation tools designed to improve radiologist efficiency. He also co-founded DiagRad Teleradiology, helping build and grow the company through a successful exit in 2019. Dr. Kuriki is active in national professional leadership in artificial intelligence and imaging informatics. He serves as Chair of the Machine Learning Education Subcommittee at the Society for Imaging Informatics in Medicine (SIIM) and contributes to AI initiatives within the Radiological Society of North America. He was also recognized among the Dallas Innovates AI 75 for his work in artificial intelligence. Throughout his career, Dr. Kuriki has combined clinical neuroradiology, hands-on software development, and artificial intelligence. His overarching goal is to move AI beyond retrospective research and proof-of-concept development into safe, scalable, and measurable clinical systems that augment physicians, improve radiology workflows, and ultimately improve patient care. In his spare time, Dr. Kuriki enjoys spending time with his family and friends, grilling Brazilian barbecue, and coding AI models. Education Medical Education Universiade Federal de Sao Paulo (2005) Residency Universiade Federal de Sao Paulo (2010) Fellowship Universiade Federal de Sao Paulo (2011) Fellowship UT Southwestern Medical Center (2024), Neuroradiology Research Interest AI for Medical Education and Quality Improvement AI Safety, Performance Monitoring, and Governance AI-Assisted Radiology Reporting Applied Artificial Intelligence in Radiology Artificial Intelligence in Neuroradiology Clinical AI Deployment and Implementation Clinical Decision Support Computer Vision in Radiology Large Language Models and Agentic AI in Healthcare Natural Language Processing in Medical Imaging Radiology Informatics and Workflow Automation Vision-Language and Multimodal Foundation Models Publications Featured Publications The RSNA Lumbar Degenerative Imaging Spine Classification (LumbarDISC) Dataset. Richards TJ, Flanders AE, Colak E, Prevedello LM, Ball RL, Kitamura F, Mongan J, Vazirabad M, Lin HM, Kendell A, Kanthawang T, Angkurawaranon S, Altinmakas E, Dogan H, Kuriki PEA, Somasundaram A, Rushton C, Bulja D, Spahovic N, Sommer J, Jiang S, Farina EMJM, Caminha Nunes E, Brassil M, McNamara M, Ortiz J, Peoples J, Uytana VL, Kam A, Dola VNS, Murphy D, Vu D, Hakim A, Talbott JF, Radiol Artif Intell 2026 Mar 8 2 e250480 Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline. Mese I, Akinci D'Antonoli T, Bluethgen C, Bressem K, Cuocolo R, Chaudhari A, Tejani AS, Isaac A, Ponsiglione A, Meddeb A, Khosravi B, Le Guellec B, Kahn CE, Suh CH, Pinto Dos Santos D, Koh DM, Tzanis E, Kotter E, Colak E, Kitamura F, Busch F, Nensa F, Yang G, Müller H, Kather JN, Nawabi J, Kleesiek J, Zhong J, Santinha J, Haubold J, de Almeida JG, Lekadir K, Marias K, Reiner LN, Maier-Hein L, Moy L, Adams LC, Martí-Bonmatí L, Paschali M, Moassefi M, Dietzel M, Huisman M, Ingrisch M, Klontzas ME, Papanikolaou N, Diaz O, Kuriki P, Seeböck P, Rouzrokh P, Strotzer QD, Park SH, Faghani S, Tayebi Arasteh S, Kim SH, Venugopal VK, Kim W, Kocak B, Diagn Interv Radiol 2026 Feb Pixel Tampering: Does Face Redaction Harm Medical AI Performance? Farina EMJM, Matsuoka FA, Corradi G, Yamagishi Y, Abe M, Pfeiffer M, Souza AS, Moreno R, Bramati I, Moll F, Bitencourt A, Sacomani C, Damião SQ, Chojniak R, Abdala N, Ragazzini R, Carrete H, Kuriki PEA, Takahashi MS, Caserta N, Nomura CH, Kitamura FC, J Imaging Inform Med 2025 Dec Seeing the Unseen: How Unsupervised Learning Can Predict Genetic Mutations from Radiologic Images. Júdice de Mattos Farina EM, Kuriki PEA, Radiol Artif Intell 2025 May 7 3 e250243 Predicting Mortality with Deep Learning: Are Metrics Alone Enough? Júdice de Mattos Farina EM, Kuriki PEA, Radiol Artif Intell 2025 May 7 3 e250224 How to Evaluate Artificial Intelligence Literature: A Concise Guide for Humans Ali S. Tejani, Yin Xi, Fernando U. Kay, Paulo Kuriki, Yee Seng Ng Roentgen Ray Review 2025 1 1 e2401033 Performance of ChatGPT on the Brazilian Radiology and Diagnostic Imaging and Mammography Board Examinations. Almeida LC, Farina EMJM, Kuriki PEA, Abdala N, Kitamura FC, Radiol Artif Intell 2024 Jan 6 1 e230103 Artificial Intelligence in Radiology: A Private Practice Perspective From a Large Health System in Latin America. Kuriki PEA, Kitamura FC, Semin Roentgenol 2023 Apr 58 2 203-207 Beyond the AJR: Patrolling k-Space to Spot "Data Crimes" Using Public MRI Datasets. Kuriki PEA, Kitamura FC, AJR Am J Roentgenol 2023 Feb 220 2 303 Editorial Comment: Cost-effectiveness of brain MRI in stroke emergency patients. de Aguiar Kuriki PE, Kitamura FC, Eur Radiol 2022 Feb 32 2 1115-1116 Results 1-10 of 11 1 2 Next Last Books Featured Books Artificial Intelligence in Neuroradiology. In Clinical Artificial Intelligence in Radiology Paulo E. A. Kuriki, Eduardo M. J. M. Farina, Felipe C. Kitamura (2026). Leesburg, VA, American Roentgen Ray Society The Sella Turcica. In Atlas of Imaging in Infertility: A Complete Guide Based on Key Images Paulo E. A. Kuriki (2017). Springer Honors & Awards Best of R3 ArticleHow to Evaluate Artificial Intelligence Literature: A Concise Guide for Humans (2025) Dallas Innovates AI75Recognized among 75 artificial intelligence leaders transforming industries across North Texas. (2025-2025) Kaggle Silver MedalGoogle Brain Ventilator Pressure Prediction Organization: Kaggle / Google Brain (2022) AI Model Showcase WinnerSociety for Imaging Informatics in Medicine (2021) Magna Cum LaudeRadiological Society of North America (2020) Professional Associations/Affiliations American Society of Neuroradiology (2022) European Radiology (2021) Radiological Society of North America (2025) Sociedade Paulista de Radiologia (2012) Society for Imaging Informatics in Medicine (2021)
