CuratioDL
Deep-learning-based Cancer Management Solutions
Company Overview
Snapshot
Founded in January 2021 by Rafi Heumann, Eran Gilboa, Prof. Jack Baniel, Prof. Yuval Shahar, and Dr. Irit Arbel, CuratioDL operates with 1–10 employees. The company has raised $817,000 across two funding rounds.
Business overview
CuratioDL specializes in cancer management solutions, leveraging deep-learning-powered pathology analysis to provide accurate diagnoses and prognoses. The company's core technology, developed at Harvard University, facilitates personalized treatment plans for cancer patients by offering expert-level decision support, particularly beneficial for pathologists who may not be specialists in a specific field. CuratioDL operates in the Health Tech & Life Sciences sector, focusing on digital healthcare, digital medical diagnostics, and serving markets that include pharmaceutical companies, insurance companies, laboratories, and healthcare providers.
Strategic signal
In September 2022, CuratioDL was highlighted for its life-saving technology aimed at early cancer diagnosis. This signals the company's potential to significantly impact the healthcare industry by improving diagnostic accuracy and enabling more timely and personalized cancer treatments, which is critical for investors looking at disruptive medical technology solutions.
Company Intelligence Q&A
- What is CuratioDL's primary focus?
- CuratioDL focuses on providing cancer management solutions through deep-learning-based pathology analysis for accurate diagnoses and prognoses, enabling personalized treatment for cancer patients.
- When was CuratioDL founded and by whom?
- CuratioDL was founded in January 2021 by Rafi Heumann, Eran Gilboa, Prof. Jack Baniel, Prof. Yuval Shahar, and Dr. Irit Arbel.
- What is the status of CuratioDL's operations?
- CuratioDL is currently non-active and ceased to operate in February 2025.
- What is the core technology behind CuratioDL's solutions?
- CuratioDL utilizes an exclusive patented technology developed at Harvard University, which employs deep-learning-powered pre-processing segmentation for pathology analysis.