Ronen Heled
3 Papers
1 Citations
Ronen Heled is an academic researcher. The author has contributed to research in topics: Medicine & Interface (computing). The author has an hindex of 1, co-authored 2 publications.
Chat about Author
Papers
An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study.
Liron Pantanowitz,Liron Pantanowitz,Gabriela Quiroga-Garza,Lilach Bien,Ronen Heled,Daphna Laifenfeld,Chaim Linhart,Judith Sandbank,Anat Albrecht Shach,Varda Shalev,Manuela Vecsler,Pamela Michelow,Scott Hazelhurst,Rajiv Dhir +13 more
- 01 Aug 2020
TL;DR: The successful development, external clinical validation, and deployment in clinical practice of an AI-based algorithm to accurately detect, grade, and evaluate clinically relevant findings in digitised slides of prostate CNBs is reported.
263
Patent
System and method for personalization and optimization of digital pathology analysis
Chaim Linhart,Lilach Bien,Ronen Heled,Joseph Mossel +3 more
- 10 Oct 2019
TL;DR: A method and system for personalization of digital pathology analysis may include an image-analysis based diagnostics module, configured to extract at least one feature of a digital scan of a pathology slide of a patient, a human-machine interface module, configurable to present the digital scan to a user for examination and at least a machine learning module, which can produce at least personalized suggestion according to the at least extracted slide feature.
1
Abstract PD11-04: A multi-feature AI-based solution for cancer diagnosis in breast biopsies: A prospective blinded multi-site clinical study
Anne Vincent-Salomon,Guillaume Bataillon,Alon Nudelman,Judith Sandbank,Anat Albrecht Shach,Lucie Thibault,Lilach Bien,Rachel Mikulinsky,Ira Krasnitsky,Ronen Heled,Chaim Linhart,Manuela Vecsler,Daphna Laifenfeld +12 more
TL;DR: This blinded multi-site study reports the successful clinical validation of a multi-feature AI-based solution in detecting and automatically imparting clinically relevant diagnostic parameters regarding invasive and in situ breast carcinoma, offering an important tool for computer-aided diagnosis in routine pathology practice.