Since its founding nine years ago, Israeli clinical decision support startup Aidoc has grown into a major player in healthcare artificial intelligence, raising $370 million and signing more than 150 contracts with health systems including Mount Sinai, Yale New Haven Health and Sutter Health. These providers use the company's platform to help radiologists quickly identify critical findings in medical scans and ensure those findings are implemented.
Timing is a key factor in Aidoc's success, Tom Valent, the company's chief commercial officer, said in an interview at the Radiological Society of North America's annual meeting in Chicago earlier this month.
He said Aidoc is benefiting from entering the market as a “second generation” medical AI company after early-stage startups like Arterys and Zebra Medical had already given providers a taste of the technology.
Valent explains that this allows Aidoc to focus more on innovation and product delivery rather than educating the market from scratch.
“The first generation is starting to become more aware and open to AI, and we are able to leverage that and focus more on execution,” he declared.
Valent said another major reason for Aidoc's success is its early focus on acute clinical use cases, which allowed the startup to quickly demonstrate its value and win the trust of providers.
“These situations are often life-or-death, so the immediate clinical outcome is very clear, rather than the long-term, proven outcome that requires in-depth clinical studies,” he commented.
He also highlighted Aidoc's R&D-first culture as its differentiating factor.
Valent noted that the company's emphasis on research and development, rather than aggressive marketing, allows Aidoc to build AI tools that integrate smoothly into clinical workflows and address the real-world complexities of healthcare environments without creating additional burden.
He noted that patient safety and quality will remain core priorities as the startup continues to develop new AI models, adding that accuracy is a key factor.
“We need to make sure that our products have high accuracy. Why? Because if their sensitivity is low, that means they're going to miss important things — if doctors start relying on it to actually classify their workflow, and our specificity is low, that means we could be generating a lot of false positives, which actually causes doctors to ignore AI,” Valent explained.
Transparency is also an important component of AI safety, he noted. Transparency is critical both before and after deployment, he said, with tools such as model cards clearly explaining how the Aidoc algorithm was trained, possible shortcomings and what clinicians should expect.
He also noted that continuous monitoring of real-world usage and performance can help ensure that AI tools are used correctly for clinical decision support.
Going forward, Valent believes Aidoc's commitment to patient safety and transparency will be key to the company's continued success.
Photo: Tom Werner, Getty Images
