Mr. Doc
Mr. Doc s.r.l. is an AI-driven diagnostic platform specializing in non-communicable diseases such as ophthalmology, cardiology, and radiology. Their technology uses advanced deep learning with active reinforcement learning to minimize human doctor effort and speed up training. Key products include Ophthal, a CE-marked software for automatic retinal OCT scan interpretation to diagnose diabetic macular edema, and AI tools for mammography and heart condition detection via smartphone video selfies. The platform is designed to work with small labeled datasets and robustly handle noisy or incomplete data, aiming to reduce healthcare costs and improve early disease detection. The company is based in Rome, Italy, and has received EU Horizon 2020 funding and support from AbbVie Srl.
Mr. Doc
Mr. Doc s.r.l. is an AI-driven diagnostic platform specializing in non-communicable diseases such as ophthalmology, cardiology, and radiology. Their technology uses advanced deep learning with active reinforcement learning to minimize human doctor effort and speed up training. Key products include Ophthal, a CE-marked software for automatic retinal OCT scan interpretation to diagnose diabetic macular edema, and AI tools for mammography and heart condition detection via smartphone video selfies. The platform is designed to work with small labeled datasets and robustly handle noisy or incomplete data, aiming to reduce healthcare costs and improve early disease detection. The company is based in Rome, Italy, and has received EU Horizon 2020 funding and support from AbbVie Srl.
TL;DR
Headquarters: Rome, Italy
Core product: Ophthal — CE-marked retinal OCT AI software
Tech focus: Semi-supervised / active reinforcement learning for medical imaging
Team size (reported): 6 employees
Public funding: EU Horizon 2020 grant (No. 876145)
Company Overview
Problem Domain
Medical imaging diagnostics for non-communicable diseases (ophthalmology, cardiology, radiology).
Industry
Healthtech / Medical AI
Funding Track Record
Project received Horizon 2020 funding (grant referenced)
Acknowledged unconditional contribution for the Ophthal project