Esteva, Andre

Dermatologist-level classification of skin cancer with deep neural networks

Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017) · Nature

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 14,362

A guide to deep learning in healthcare

Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G., Thrun, S., & Dean, J. (2019) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 5,312

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

Liu, X., Cruz Rivera, S., Moher, D., Calvert, M. J., Denniston, A. K., The SPIRIT-AI and CONSORT-AI Working Group, SPIRIT-AI and CONSORT-AI Steering Group, Chan, A.-W., Darzi, A., Holmes, C., et al. (2020) · Nature Medicine

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

Cited by 1,421

Deep learning-enabled medical computer vision

Esteva, A., Chou, K., Yeung, S., Naik, N., Madani, A., Mottaghi, A., Liu, Y., Topol, E., Dean, J., & Socher, R. (2021) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationAdvanced Neural Network Applications

Cited by 1,406

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Vasey, B., Nagendran, M., Campbell, B., Clifton, D. A., Collins, G. S., Denaxas, S., Denniston, A. K., Faes, L., Geerts, B., Ibrahim, M., et al. (2022) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 1,039

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

Cruz Rivera, S., Liu, X., Chan, A.-W., Denniston, A. K., Calvert, M. J., The SPIRIT-AI and CONSORT-AI Working Group, SPIRIT-AI and CONSORT-AI Steering Group, Darzi, A., Holmes, C., Yau, C., et al. (2020) · Nature Medicine

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

Cited by 933

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images

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., et al. (2018) · Cell

Cell Image Analysis TechniquesAdvanced Fluorescence Microscopy Techniques

Cited by 635

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

Liu, X., Cruz Rivera, S., Moher, D., Calvert, M. J., Denniston, A. K., Ashrafian, H., Beam, A. L., Chan, A.-W., Collins, G. S., Deeks, A. D. J., et al. (2020) · The Lancet Digital Health

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

Cited by 555

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

Cruz Rivera, S., Liu, X., Chan, A.-W., Denniston, A. K., Calvert, M. J., Ashrafian, H., Beam, A. L., Collins, G. S., Darzi, A., Deeks, J. J., et al. (2020) · The Lancet Digital Health

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

Cited by 486

Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials

Esteva, A., Feng, J., van der Wal, D., Huang, S.-C., Simko, J. P., DeVries, S., Chen, E., Schaeffer, E. M., Morgan, T. M., Sun, Y., et al. (2022) · npj Digital Medicine

Radiomics and Machine Learning in Medical ImagingAI in cancer detection

Cited by 217

A mountable toilet system for personalized health monitoring via the analysis of excreta

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., et al. (2020) · Nature Biomedical Engineering

Non-Invasive Vital Sign MonitoringBiosensors and Analytical Detection

Cited by 175

Artificial intelligence predictive model for hormone therapy use in prostate cancer

Spratt, D. E., Tang, S., Sun, Y., Huang, H.-C., Chen, E., Mohamad, O., Armstrong, A. J., Tward, J. D., Nguyen, P. L., Lang, J. M., et al. (2023) · NEJM Evidence

Prostate Cancer Diagnosis and TreatmentRadiomics and Machine Learning in Medical Imaging

Cited by 153

Two distinct scene processing networks connecting vision and memory

Baldassano, C., Esteva, A., Fei-Fei, L., & Beck, D. M. (2016) · eneuro

Memory and Neural MechanismsVisual perception and processing mechanisms

Cited by 144

Best practices for authors of healthcare-related artificial intelligence manuscripts

Kakarmath, S., Esteva, A., Arnaout, R., Harvey, H., Kumar, S., Muse, E., Dong, F., Wedlund, L., & Kvedar, J. (2020) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationAcademic Writing and Publishing

Cited by 46

External validation of a digital pathology-based multimodal artificial intelligence architecture in the NRG/RTOG 9902 phase 3 trial

Ross, A. E., Zhang, J., Huang, H.-C., Yamashita, R., Keim-Malpass, J., Simko, J. P., DeVries, S., Morgan, T. M., Souhami, L., Dobelbower, M. C., et al. (2024) · European Urology Oncology

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 35

Validation of an artificial intelligence-based prognostic biomarker in patients with oligometastatic Castration-Sensitive prostate cancer

Wang, J. H., Deek, M. P., Mendes, A. A., Song, Y., Shetty, A., Bazyar, S., Van der Eecken, K., Chen, E., Showalter, T. N., Royce, T. J., et al. (2025) · Radiotherapy and Oncology

Prostate Cancer Treatment and ResearchRadiomics and Machine Learning in Medical Imaging

Cited by 25