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Aidoc eyes IPO following Goldman-led $150M raise
The big picture: Radiology is one of AI's earliest and most established use cases at scale in health care. Follow the money: Goldman Sachs Alternatives' growth equity division led the round. General Catalyst, SoftBank Investment Advisors and NVentures, NVIDIA's venture capital arm, joined. *
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Nvidia's NVentures backs $150M round for medical AI startup Aidoc - SiliconANGLE
Nvidia's NVentures backs $150M round for medical AI startup Aidoc Aidoc Medical Ltd., a startup with an artificial intelligence platform that helps doctors diagnose patients faster, has secured $150 million in funding. Goldman Sachs led the Series C round. Aidoc stated in its funding announcement
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Medical AI provider Aidoc secured $150 million in a Goldman Sachs-led funding round, with participation from Nvidia's NVentures, General Catalyst, and SoftBank Investment Advisors. The company, which has now raised $520 million total, plans to use proceeds for regulatory approvals and building comprehensive AI models while targeting an IPO in three to five years.
Aidoc has closed a $150 million funding round led by Goldman Sachs Alternatives' growth equity division, marking a significant milestone for the medical AI company as it prepares for a potential public offering
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. The Goldman Sachs-led funding attracted participation from Nvidia's NVentures, General Catalyst, and SoftBank Investment Advisors, bringing Aidoc's total capital raised to $520 million1
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. While the company declined to disclose its valuation, CEO Elad Walach indicated that Aidoc aims to IPO within three to five years1
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Source: SiliconANGLE
The company's aiOS platform leverages a proprietary foundation model called the Clinical AI Reasoning Engine (CARE) that represents a departure from traditional single-purpose medical AI systems
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. Unlike clinical-grade AI models historically trained to process only one type of medical data, CARE can analyze medical imaging including CT scans and X-rays, electronic health records, patient vitals, and lab results2
. The platform's AI capabilities enable it to read and flag incidental findings on CT scans, supporting critical use cases such as emergency department triage and identifying abnormalities on abdominal scans, including liver and spleen injuries and appendicitis1
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Source: Axios
Aidoc has secured 31 FDA clearances for various use cases ranging from emergency department triage to detecting conditions on abdominal scans
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. In January, the U.S. Food and Drug Administration cleared CARE for diagnostic tasks across 11 disease indicators, adding to three other indicators previously approved2
. The company reports that CARE achieves specificity of up to 99.7%, corresponding to less than 1% chance of false positives—approximately an order of magnitude better than some competing models2
. The algorithm's mean specificity across the 11 FDA-approved disease indicators stands at 98%2
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Proceeds from the funding round will help Aidoc navigate the notoriously expensive regulatory approval process and invest in building a large, comprehensive AI model, according to Walach
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. The dually headquartered company in Israel and New York has built a foundation model that allows customers to deploy tools from third-party companies, expanding its platform's flexibility1
. Aidoc's platform is currently installed in nearly 2,000 hospitals worldwide, where medical teams use it to process data about more than 60 million patients per year2
.Aidoc faces competition from both incumbents and startups as dealmaking in the medical imaging space continues to accelerate. GE HealthCare has made multiple acquisitions since spinning off from GE, completing a $2.3 billion acquisition of Intelerad last month
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. Siemens Healthineers launched its own radiology services suite designed to assist providers with scheduling, reporting, and image generation last year1
. RadAI raised a $60 million Series C last month led by Transformation Capital, achieving a valuation of $525 million1
. The competitive landscape suggests that AI-powered diagnostics will continue attracting significant investment as healthcare systems seek to improve efficiency and patient outcomes.Summarized by
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