Andre Esteva
- Health Informatics top 0.01%
- Artificial Intelligence in Healthcare and Education 3
- Health Information Management top 0.05%
-
- Radiomics and Machine Learning in Medical Imaging 12
- Artificial Intelligence top 0.1%
- AI in cancer detection 10
- Biophysics top 0.2%
- Cell Image Analysis Techniques 4
-
- Prostate Cancer Treatment and Research 9
- Prostate Cancer Diagnosis and Treatment 7
-
- Cutaneous Melanoma Detection and Management 5
-
- Image Retrieval and Classification Techniques 3
Andre Esteva
27 papers receiving 11.5k citations
Hit Papers
Peers
Comparison fields: 5 of 205
- Health Informatics 2.0k
- Health Information Management 782
- Radiology, Nuclear Medicine and Imaging 3.6k
- Artificial Intelligence 4.9k
- Biophysics 830
Countries citing papers authored by Andre Esteva
This map shows the geographic impact of Andre Esteva's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andre Esteva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andre Esteva more than expected).
Fields of papers citing papers by Andre Esteva
This network shows the impact of papers produced by Andre Esteva. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andre Esteva. The network helps show where Andre Esteva may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Andre Esteva, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 1 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 7 | |
| 10 | 2021 | 24 | |
| 11 | 2021 | 16 | |
| 12 | Deep learning-enabled medical computer visionbreakdown → | 2021 | 718 |
| 13 | 2018 | 40 | |
| 14 | In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Imagesbreakdown → | 2018 | 394 |
| 15 | A guide to deep learning in healthcarebreakdown → | 2018 | 2350 |
| 16 | Dermatologist-level classification of skin cancer with deep neural networksbreakdown → | 2017 | 7941 |
| 17 | Skin Cancer Detection and Tracking using Data Synthesis and Deep Learning | 2016 | 2 |
| 18 | 2016 | 106 | |
| 19 | 2015 | 1 | |
| 20 | 2015 | 54 |
About Andre Esteva
Andre Esteva is a scholar working on Health Informatics, Biophysics and Radiology, Nuclear Medicine and Imaging, having authored 30 papers that have together received 11.9k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (12 papers), AI in cancer detection (10 papers), Prostate Cancer Treatment and Research (9 papers), Prostate Cancer Diagnosis and Treatment (7 papers), Cutaneous Melanoma Detection and Management (5 papers), Cell Image Analysis Techniques (4 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Image Retrieval and Classification Techniques (3 papers). The work is most often cited by research in Health Informatics (2.0k citations), Health Information Management (782 citations) and Radiology, Nuclear Medicine and Imaging (3.6k citations). Andre Esteva has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Sebastian Thrun, Justin Ko, Roberto A. Novoa, Helen M. Blau, Susan M. Swetter, Jeff Dean, Katherine Chou, Bharath Ramsundar, Claire Cui and Greg S. Corrado. Their work appears in journals such as Journal of Clinical Oncology, npj Digital Medicine, Journal of Vision, Journal of Investigative Dermatology and Clinical Cancer Research.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.