User profiles for A. Esteva
Andre EstevaCo-Founder & CEO, Artera Verified email at artera.ai Cited by 19118 |
[HTML][HTML] Deep learning-enabled medical computer vision
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential
for many fields—including medicine—to benefit from the insights that AI techniques can …
for many fields—including medicine—to benefit from the insights that AI techniques can …
[HTML][HTML] Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
…, MK ElZarrad, C Espinoza, A Esteva… - The Lancet Digital …, 2020 - thelancet.com
The CONSORT 2010 statement provides minimum guidelines for reporting randomised trials.
Its widespread use has been instrumental in ensuring transparency in the evaluation of …
Its widespread use has been instrumental in ensuring transparency in the evaluation of …
[HTML][HTML] Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
…, MK ElZarrad, C Espinoza, A Esteva… - The Lancet Digital …, 2020 - thelancet.com
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol
reporting by providing evidence-based recommendations for the minimum set of items to be …
reporting by providing evidence-based recommendations for the minimum set of items to be …
Dermatologist-level classification of skin cancer with deep neural networks
Skin cancer, the most common human malignancy 1, 2, 3, is primarily diagnosed visually,
beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a …
beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a …
[PDF][PDF] In silico labeling: predicting fluorescent labels in unlabeled images
Microscopy is a central method in life sciences. Many popular methods, such as antibody
labeling, are used to add physical fluorescent labels to specific cellular constituents. However, …
labeling, are used to add physical fluorescent labels to specific cellular constituents. However, …
A guide to deep learning in healthcare
Here we present deep-learning techniques for healthcare, centering our discussion on
deep learning in computer vision, natural language processing, reinforcement learning, and …
deep learning in computer vision, natural language processing, reinforcement learning, and …
[HTML][HTML] COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization
The COVID-19 global pandemic has resulted in international efforts to understand, track,
and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2-related …
and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2-related …
Correction: Corrigendum: Dermatologist-level classification of skin cancer with deep neural networks
In the Acknowledgements section of this Letter, the sentence:“This study was supported by
the Baxter Foundation, California Institute for Regenerative Medicine (CIRM) grants TT3-…
the Baxter Foundation, California Institute for Regenerative Medicine (CIRM) grants TT3-…
[HTML][HTML] Deep learning-enabled breast cancer hormonal receptor status determination from base-level H&E stains
For newly diagnosed breast cancer, estrogen receptor status (ERS) is a key molecular
marker used for prognosis and treatment decisions. During clinical management, ERS is …
marker used for prognosis and treatment decisions. During clinical management, ERS is …
[HTML][HTML] Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials
Prostate cancer is the most frequent cancer in men and a leading cause of cancer death.
Determining a patient’s optimal therapy is a challenge, where oncologists must select a therapy …
Determining a patient’s optimal therapy is a challenge, where oncologists must select a therapy …