- American Society of Neuroradiology (2022), International Member
- European Radiology (2021), Reviewer
- Society for Imaging Informatics in Medicine (2021), Machine Learning Education Subcommittee Member
- Sociedade Paulista de Radiologia (2012), Machine Learning Committee Member
- Radiological Society of North America (2006), Member and AI Reviewer
Paulo De Aguiar Kuriki, M.D.
- Radiology - Neuroradiology
Biography
Paulo E. A. Kuriki, M.D., is an Assistant Professor at UT Southwestern Medical Center and a member of its Neuroradiology Division. He is a practicing neuroradiologist with expertise in imaging of the brain, spine, and head and neck, including advanced MRI and imaging evaluation of neurologic, neurosurgical, and oncologic conditions.
In addition to his clinical practice, Dr. Kuriki is Director of the Artificial Intelligence in Radiology Hub (AIR-Hub) at UT Southwestern. His work in artificial intelligence is closely connected to his clinical experience and focuses on developing and implementing technologies that support radiologists, improve diagnostic workflows, and enhance the quality and efficiency of patient care.
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.
Dr. Kuriki's academic interests include artificial intelligence in neuroradiology, imaging informatics, computer vision, natural language processing, large language models, multimodal AI, and the implementation of AI systems in clinical practice. At UT Southwestern, his team develops AI-enabled tools for radiology reporting, imaging protocol optimization, quality improvement, and other clinical applications.
Dr. Kuriki is active in national professional organizations focused on radiology, imaging informatics, and artificial intelligence. 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 and the American Society of Neuroradiology.
In addition to his clinical and academic work, Dr. Kuriki has experience as a healthcare entrepreneur and co-founded DiagRad Teleradiology, which later completed a successful merger.
In his spare time, Dr. Kuriki enjoys spending time with his family and friends, grilling Brazilian barbecue, and coding AI models.
Education & Training
- Medical Education - Universiade Federal de Sao Paulo (1999-2005)
- Residency - Universiade Federal de Sao Paulo (2007-2010)
- Fellowship - Universiade Federal de Sao Paulo (2010-2011)
- Fellowship - UT Southwestern Medical Center (2023-2024), Neuroradiology
Professional Associations & Affiliations
Honors & Awards
- AI Model Showcase Winner 2021, Society for Imaging Informatics in Medicine
- Magna Cum Laude 2020, Radiological Society of North America
Books & Publications
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Publications
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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, Radiology. Artificial intelligence 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, Diagnostic and interventional radiology (Ankara, Turkey) 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, Journal of imaging informatics in medicine 2025 Dec -
Predicting Mortality with Deep Learning: Are Metrics Alone Enough?
Júdice de Mattos Farina EM, Kuriki PEA, Radiology. Artificial intelligence 2025 May 7 3 e250224 -
Seeing the Unseen: How Unsupervised Learning Can Predict Genetic Mutations from Radiologic Images.
Júdice de Mattos Farina EM, Kuriki PEA, Radiology. Artificial intelligence 2025 May 7 3 e250243 -
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, Radiology. Artificial intelligence 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, Seminars in roentgenology 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. American journal of roentgenology 2023 Feb 220 2 303 -
Editorial Comment: Cost-effectiveness of brain MRI in stroke emergency patients.
de Aguiar Kuriki PE, Kitamura FC, European radiology 2022 Feb 32 2 1115-1116 -
Machine learning model for predicting severity prognosis in patients infected with COVID-19: Study protocol from COVID-AI Brasil.
Paiva Proença Lobo Lopes F, Kitamura FC, Prado GF, Kuriki PEA, Garcia MRT, PloS one 2021 16 2 e0245384
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The RSNA Lumbar Degenerative Imaging Spine Classification (LumbarDISC) Dataset.