Cloud-based startup Segmed raises $2m to advance dataset sharing for medical AI

Cloud-based startup Segmed raises $2m to advance dataset sharing for medical AI

Published: 02-12-2020 15:14:00 | By: Pie Kamau | hits: 4319 | Tags:

Segmed, a cloud-based platform that curates medical data by anonymizing, standardizing and labeling, to accelerate innovation in healthcare, closed $2 million dollars in seed funding led by Blumberg Capital with participation from Nina Capital and other angel investors.

The healthcare industry is generating data at an unprecedented rate but unless this data is standardized, labeled and curated for use by patients, clinicians and researchers, it is of little use. Proper sourcing and preparation of data with precise, high-quality labels is a costly, error prone and lengthy process. Segmed's solution automates and streamlines the process and provides valuable, high-quality training datasets for AI models. The solution shortens time to market for AI developers and generates new revenue streams for hospitals by monetizing medical data securely and anonymously.

Cailin Hardell, Co-founder and CEO, Segmed: "We aim to aggregate and leverage larger and more representative datasets for use in medical AI to ultimately deliver better healthcare around the world. Medical AI has the potential to improve diagnostics, predictive and preventative medicine for quality patient care while reducing cost to address underserved populations around the world. Segmed helps ensure that the broadest datasets are available to medical AI application developers and clinicians to deliver better products and services that can best serve the most patients."

Patient privacy and data security are top priorities at Segmed. The company maintains strict HIPAA compliance and only uses and shares data that is fully anonymized, ensuring that no personal information is ever exposed.

David Blumberg, Founder and Managing Partner, Blumberg Capital: "The healthcare industry has increasingly adopted the use of AI in recent years and the rapid response of medical researchers and practitioners to the COVID-19 crisis has demonstrated its value. By fast-tracking the training data used to develop medical AI algorithms, Segmed aggregates, simplifies and speeds the difficult process of sourcing data from individual hospitals for use by pharmaceutical and medical device companies, clinicians, researchers and CROs, among others. Harnessing medical data in AI models will yield insights, identify patterns, improve outcomes, lower costs and revolutionize healthcare."