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Renato Umeton, PhD

Renato Umeton, PhD

  • Vice President of Data Sciences and Chief of Artificial Intelligence

Education

  • PhD (Mathematics and Informatics) – University of Calabria, Italy
  • MS (Computer Science) – University of Calabria, Italy
  • BS (Computer Science) – University of Calabria, Italy

Research Interests

  • Artificial Intelligence in Healthcare
  • Data Science in Healthcare
  • Machine Learning in Healthcare
  • Optimization in Healthcare
  • Computer Science in Healthcare

Selected Publications

Gallifant J, Afshar M, Ameen S, Aphinyanaphongs Y, Chen S, Cacciamani G, Demner-Fushman D, Dligach D, Daneshjou R, Fernandes C, Hansen LH, Landman A, Lehmann L, McCoy LG, Miller T, Moreno A, Munch N, Restrepo D, Savova G, Umeton R, Gichoya JW, Collins GS, Moons KGM, Celi LA, Bitterman DS. The TRIPOD-LLM reporting guideline for studies using large language models. Nature Medicine, 2025. 

Mechelli R, Umeton R, Bellucci G, Bigi R, Rinaldi V, et al. A disease-specific convergence of host and Epstein-Barr virus genetics in multiple sclerosis. Proceedings of the National Academy of Sciences, 2025. 

Kassem H, Singh A, Aristizabal A, Bakas S, Sheller M, Umeton R, Pati S, et al. Chapter 9 - Collaborative evaluation for performance assessment of medical imaging applications. (Book) Trustworthy AI in Medical Imaging, 2025.

Umeton R, Kwok A, Maurya R, Leco D, Lenane N, et al. GPT-4 in a cancer center - institute-wide deployment challenges and lessons learned. NEJM AI, 2024. 

Omar M, Ullanat V, Loda M, Marchionni L, Umeton R. ChatGPT for digital pathology research. The Lancet Digital Health, 2024. 

Ricciuti B, Lamberti G, Puchala SR, Mahadevan NR, Lin JR, Alessi JV, Chowdhury A, Li YY, Wang X, Spurr L, Pecci F, Di Federico A, Venkatraman D, Barrichello AP, Gandhi M, Vaz VR, Pangilinan AJ, Haradon D, Lee E, Gupta H, Pfaff KL, Welsh EL, Nishino M, Cherniack AD, Johnson BE, Weirather JL, Dryg ID, Rodig SJ, Sholl LM, Sorger P, Santagata S, Umeton R, Awad MM. Genomic and immunophenotypic landscape of acquired resistance to PD-(L)1 blockade in non-small-cell lung cancer. Journal of Clinical Oncology, 2024. 

Karargyris A, Umeton R, Sheller MJ, Aristizabal A, George J, et al. Federated benchmarking of medical artificial intelligence with MedPerf. Nature Machine Intelligence, 2023. 

Placido D, Yuan B, Hjaltelin JX, Zheng C, Haue AD, et al. A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories. Nature Medicine, 2023. 

Pati S, Thakur SP, Hamamcı IE, Baid U, Baheti B, Bhalerao M, Güley O, Mouchtaris S, Lang D, Thermos S, Gotkowski K, González C, Grenko C, Getka A, Edwards B, Sheller M, Wu J, Karkada D, Panchumarthy R, Ahluwalia V, Zou C, Bashyam V, Li Y, Haghighi B, Chitalia R, Abousamra S, Kurc TM, Gastounioti A, Er S, Bergman M, Saltz JH, Fan Y, Shah P, Mukhopadhyay A, Tsaftaris SA, Menze B, Davatzikos C, Kontos D, Karargyris A, Umeton R, Mattson P, Bakas S. GaNDLF: The generally nuanced deep learning framework for scalable end-to-end clinical workflows. Communications Engineering, 2023.

Umeton R, Bellucci G, Bigi R, Romano S, Buscarinu MC, Reniè R, et al. Multiple sclerosis genetic and non-genetic factors interact through the transient transcriptome. Scientific Reports, 2022. 

Ricciuti B, Wang X, Alessi JV, Rizvi H, Mahadevan NR, et al. Association of high tumor mutation burden in non-small cell lung cancers with increased immune infiltration and improved clinical outcomes of PD-L1 blockade. JAMA Oncology, 2022.

Rosenthal J, Carelli R, Omar M, Brundage D, Halbert E, Nyman J, Hari SN, et al. Building tools for machine learning and artificial intelligence in cancer research: best practices and a case study with the PathML toolkit for computational pathology. Molecular Cancer Research, 2022. 

Bychkovsky BL, Li T, Sotelo J, Tayob N, Mercado J, et al. Identification and management of pathogenic variants in BRCA1, BRCA2, and PALB2 in a tumor-only genomic testing program. Clinical Cancer Research, 2022. 

Ricciuti B, Recondo G, Spurr LF, Li YY, Lamberti G, et al. Impact of DNA damage response and repair gene mutations on efficacy of PD-(L)1 immune checkpoint inhibition in non-small cell lung cancer. Clinical Cancer Research, 2020. 

Barroso-Sousa R, Keenan TE, Pernas S, Exman P, Jain E, et al. Tumor mutational burden and PTEN alterations as molecular correlates of response to PD-1/L1 blockade in metastatic triple-negative breast cancer. Clinical Cancer Research, 2020. 

Recondo G, Bahcall M, Spurr LF, Che J, Ricciuti B, et al. Molecular mechanisms of acquired resistance to MET tyrosine kinase inhibitors in patients with MET exon 14-mutant NSCLC. Clinical Cancer Research, 2020. 

Nassar AH, Umeton R, Kim J, Lundgren K, Harshman L, et al. Mutational analysis of 472 urothelial carcinoma across grades and anatomic sites. Clinical Cancer Research, 2019. 

Vokes NI, Liu D, Ricciuti B, Jimenez-Aguilar E, Rizvi H, et al. Harmonization of tumor mutational burden quantification and association with response to immune checkpoint blockade in non-small-cell lung cancer. JCO Precision Oncology, 2019. 

Ricciuti B, Kravets S, Dahlberg SE, Umeton R, Albayrak A, et al. Use of targeted next generation sequencing to characterize tumor mutational burden and efficacy of immune checkpoint inhibition in small cell lung cancer. Journal for ImmunoTherapy of Cancer, 2019. 

Dunn IF, Du Z, Touat M, Sisti MB, Wen PY, et al. Mismatch repair deficiency in high-grade meningioma: a rare but recurrent event associated with dramatic immune activation and clinical response to PD-1 blockade. JCO Precision Oncology, 2018. 

Full list of publications

Last update: May 2025

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