Andre Esteva

Andre Esteva is an American researcher and entrepreneur in the field of medical artificial intelligence (AI). He is the co-founder and Chief Executive Officer (CEO) of ArteraAI, a company that develops AI tools for cancer therapy.

Biography

Esteva was born in Houston, Texas. He was raised in Mexico and later moved to Plano, Texas, where he graduated from Plano Senior High School.

Esteva earned Bachelor of Science degrees in Electrical and Computer Engineering and in Pure Mathematics from the University of Texas at Austin, where he received the Engineering Valedictorian award. At UT Austin, he tutored high school and undergraduate students in mathematics and physics, participated in First-Year Interest Groups as a peer mentor, and was a member of Engineers Without Borders and the Tau Beta Pi Engineering Honor Society. As an undergraduate researcher, he worked in multiple laboratories, contributing to a visible light wireless communication system and developing a MATLAB-based algorithm for analyzing nuclear growth in precancerous cells. He also studied and interned abroad in Toulouse, France.

Esteva earned a Master of Science in Electrical Engineering from Stanford University in 2015. He then pursued a Ph.D. in Electrical Engineering, focusing on machine learning and deep learning at the Stanford Artificial Intelligence Lab under the supervision of Sebastian Thrun and Stephen P. Boyd.

In 2021, Esteva co-founded ArteraAI, where he serves as CEO.

Esteva's research focuses on machine learning and deep learning in medical and biological systems. He co-authored a 2017 Nature paper, “Dermatologist-level classification of skin cancer with deep neural networks,” which reported that a deep learning model classified images of skin lesions with accuracy comparable to that of board-certified dermatologists.

Publication

Esteva has authored peer-reviewed publications. His most cited works include:

• Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118.
• Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G., Thrun, S., & Dean, J. (2019). A guide to deep learning in healthcare. Nature Medicine, 25(1), 24–29.
• Taylor, M., Liu, X., Denniston, A., Esteva, A., Ko, J., Daneshjou, R., & Chan, A.-W. (2021). Raising the bar for randomized trials involving artificial intelligence: the SPIRIT-Artificial Intelligence and CONSORT-Artificial Intelligence guidelines. Journal of Investigative Dermatology, 141(9), 2109–2111.
• Esteva, A., Michalski, J. M., & Al, E. (n.d.). Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. Digital Commons at Washington University.
• Holste, G., van der Wal, D., Pinckaers, H., Yamashita, R., Mitani, A., & Esteva, A. (2023). Improved Multimodal Fusion for Small Datasets with Auxiliary Supervision. In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) (pp. 1–5). IEEE.
• Park, S.-M., Won, D. D., Lee, B. J., Escobedo, D., Esteva, A., Aalipour, A., Ge, T. J., Kim, J. H., Suh, S., Choi, E. H., Lozano, A. X., Yao, C., Bodapati, S., Achterberg, F. B., Kim, J., Park, H., Choi, Y., Kim, W. J., Yu, J. H., Bhatt, A. M., Lee, J. K., Spitler, R., Wang, S. X., & Gambhir, S. S. (2020). Publisher Correction: A mountable toilet system for personalized health monitoring via the analysis of excreta. Nature Biomedical Engineering, 4(6), 662.
• Esteva, A., Kale, A., Paulus, R., Hashimoto, K., Yin, W., Radev, D., & Socher, R. (2021). COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization. npj Digital Medicine, 4(1), Article 68.
• Li, Y., Esteva, A., Kuprel, B., Novoa, R., Ko, J., & Thrun, S. (2016). Skin Cancer Detection and Tracking using Data Synthesis and Deep Learning. arXiv:1612.01074.
• Tward, J. D., Huang, H.-C., Esteva, A., Mohamad, O., Van Der Wal, D., Simko, J. P., DeVries, S., Zhang, J., Joun, S., Showalter, T. N., Schaeffer, E. M., Morgan, T. M., Monson, J. M., Wallace, J. A., Bahary, J.-P., Sandler, H. M., Spratt, D. E., Rodgers, J. P., Feng, F. Y., & Tran, P. T. (2024). Prostate cancer risk stratification in NRG Oncology Phase III randomized trials using multimodal deep learning with digital histopathology. JCO Precision Oncology, (8).
• Christiansen, E. M., Yang, S. J., Ando, D. M., Javaherian, A., Skibinski, G., Lipnick, S., Mount, E., O’Neil, A., Shah, K., Lee, A. K., Goyal, P., Fedus, W., Poplin, R., Esteva, A., Berndl, M., Rubin, L. L., Nelson, P., & Finkbeiner, S. (2018). In silico labeling: Predicting fluorescent labels in unlabeled images. Cell, 173(3), 792–803.e19.

Awards and recognition

• Outstanding Scholar-Leader Award, University of Texas at Austin (2011)
• TIME100 Health 2025 honoree

References

This article "Andre Esteva" is from Wikipedia. The list of its authors can be seen in its historical and/or the page Edithistory:Andre Esteva. Articles copied from Draft Namespace on Wikipedia could be seen on the Draft Namespace of Wikipedia and not main one.

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