Gesund.ai empowers medical AI developers to establish, optimize, and sustain their AI lifecycles, ensuring privacy, compliance, speed, and scalability.

Gesund.ai

Gesund.ai | 1,678 followers on LinkedIn. highway to clinical-grade AI | Gesund, a CB Insights AI 100 company, is the world’s first compliant AI factory on a mission to help bring clinical-grade AI solutions to market. To comply with regulatory requirements, our platform audits and validates 3rd party medical AI solutions for safety, effectiveness and equity. 

Backed by marquee investors including Merck, McKesson, Northpond and 500, Gesund orchestrates the entire AI/ML lifecycle for all stakeholders by bringing models, data and experts together in a no-code environment.

CBO & Board Advisor | Building AI Partnerships & Businesses | RWE | Medical Imaging | AI | AI Regulation | Oncology | Innovation | FDA | CHAI AI…

Marco Smit

CEO at Gesund

Enes Hoşgör, Ph.D.

CMO, Gesund.ai | Director, Division of Community Radiology Specialists, Emory

Sumir Patel, MD, MBA

UI/UX Designer @ Gesund.ai

Melis Yilmaz

See you all in Chicago for Radiological Society of North America (RSNA) 2024 in a couple of weeks. Make sure to come by our booth 5950 to check out our latest AI assurance platform that streamlines your FDA validation studies. Enes Hoşgör, Ph.D. Marco Smit Sumir Patel, MD, MBA Coalition for Health AI (CHAI) Demetri Giannikopoulos Prem Batchu-Green DPT, MBA,HEOR-C Brenton Hill, JD, MHA Digital Medicine Society (DiMe) VALID AI CancerX Moonshot

Implementation of trustworthy AI requires cross-stakeholder partnering. Excited (re)join forces with Digital Medicine Society (DiMe) on this monumental work!

Enes Hoşgör, Ph.D. , CEO & Founder of Gesund.ai , joins Steven Haken for our newest podcast. Enes, an engineer by training and an AI entrepreneur by trade, is driven to unlock scientific and technological breakthroughs having built AI products and companies in the last 10+ years in high-compliance environments. He illustrates that Gesund.ai are very keen to see the role of AI develop within healthcare systems and describes how they work to very stringent standards that will ensure complete protection of customer data to verify security, privacy and compliance controls. In this podcast, Enes explains how AI is enabling multi-disciplinary teams to work together more productively and efficiently. He introduces us to Gesund.ai , a prominent AI Assurance Platform designed for regulatory compliance that considers the entire AI-enabled medical device lifecycle. Watch the podcast to find out more. VALID AI CancerX Moonshot Trillium Health Partners American Heart Association Coalition for Health AI (CHAI) Veysel Kocaman, PhD Marco Smit Sumir Patel, MD, MBA . Vance Moore Özkan Uysal Jennifer Goldsack #medtech #healthcare #health #AI #innovation #compliance #podcast

Odelle Technology

Are you at HLTH USA ? Visit the Coalition for Health AI (CHAI) booth 4611 at the AI Pavilion now to meet Enes Hoşgör, Ph.D. and Marco Smit as we showcase our AI assurance lab and platform. Brenton Hill, JD, MHA Brian Anderson, MD Sumanth Ratna Ed Middleton

Kicking off HLTH USA following prolific discussions at the Coalition for Health AI (CHAI) Summit over the weekend, we are thrilled to now announce that we are open-sourcing our AI validation library compatible with virtually all FDA -regulated AI model evaluation efforts. The field of AI validation is swiftly evolving and hinges on cross-community collaboration to create the necessary trust and drive the adoption of responsible AI. By open-sourcing our library we will work with clinical, academic, scientific and regulatory communities to advance this critical field while also supporting underprivileged AI stakeholders, e.g., community hospitals, who might lack the necessary data science teams or infrastructure for AI assurance. https://lnkd.in/d3bhUfjt GitHub link here: https://lnkd.in/d4MiyYh8 VALID AI Digital Medicine Society (DiMe) CancerX Moonshot National Institute of Standards and Technology (NIST) American Heart Association Medical Device Innovation Consortium (MDIC) AFDO/RAPS Healthcare Products Collaborative Epic UL Solutions NCQA CB Insights STAT HIT Consultant Media Brenton Hill, JD, MHA Brian Anderson, MD Jennifer Goldsack Vance Moore Jithesh Veetil, PhD Casey Ross Troy Tazbaz Micky Tripathi Stephen Konya Curtis Langlotz Anura Fernando Brad Genereaux Joe Zaccaria Vik Wadhwani Oguz Akin, MD, FACR Rajath Soans Daniel Yang, MD Demetri Giannikopoulos Carl v. Gall Nabile Safdar Amir A. Khan aldo badano David Rhew, M.D. Kian Beyzavi, PhD

We are very excited to be joined by some of the leading organizations implementing and evaluating AI at our AI Pavilion Booth at HLTH. Please come by and see how Mercy , Mayo Clinic , EBSCO Health Care , University of Maryland Medical System , and Nao Innovation Lab have started applying our Assurance Standards Guide and Reporting Checklists to help with responsible AI creation and adoption. Find the documents here: https://lnkd.in/gu_R6Wkv We will also be showcasing for the first time the concept of quality assurance labs with Dandelion Health , Mayo Clinic Platform , Qualified Health , Gesund.ai , and BeeKeeperAI . Our team will also be there to field any membership questions. Looking forward to seeing you at #HLTHUSA ! Byron Yount, PhD , Elliott Green , Hailey H. , Justin Norden, MD, MBA, MPhil , Brenna Loufek , Lauren Rost, PhD , Katherine Eisenberg, MD, PhD, FAAFP , Marco Smit , Enes Hoşgör, Ph.D. , Arihant Jain , Mary Beth Chalk , Michael Blum, MD , Warren D'Souza #responsibleAI #HealthCommunity #CHAIGlobalSummit24

Coalition for Health AI (CHAI)

See you all at HLTH USA 2024 in Vegas in a few weeks! Make sure to swing by our booth at the Digital Medicine Society (DiMe) Pavilion and attend our presentation at the Coalition for Health AI (CHAI) Global Summit showcasing our FDA -focused AI assurance platform. Reach out to schedule an on-site meeting with our team Enes Hoşgör, Ph.D. , Marco Smit and Sumir Patel, MD, MBA and stay tuned for some major news in the meantime! CancerX Moonshot VALID AI American Heart Association Health AI Partnership Advanced Research Projects Agency for Health (ARPA-H)

Paper alert! Reader and annotation management for AI model development can be highly tedious and meandering potentially generating uncertain outcomes downstream in model performance across patient sub-cohorts. We demonstrated this in a recent study using real-world data and US-board-certified radiologists, led by Sumir Patel, MD, MBA , Veysel Kocaman, Ph.D. and Enes Hoşgör, Ph.D. . We are thrilled that this important research has been accepted to Society for Imaging Informatics in Medicine (SIIM) 's upcoming Conference on Machine Intelligence in Medical Imaging held in Boston University , October 21-22nd. Variability is inherent across patients, readers and model versions - the only way to tame variability is to utilize MLOps tools like Gesund.ai 's that promote transparency, traceability and cross-functional collaboration. CancerX Moonshot Digital Medicine Society (DiMe) VALID AI Coalition for Health AI (CHAI) American Heart Association National Institute of Standards and Technology (NIST) Advanced Research Projects Agency for Health (ARPA-H) Radiological Society of North America (RSNA) American College of Cardiology American College of Radiology Office for Civil Rights, Department of Health and Human Services Assistant Secretary for Technology Policy FDA U.S. Department of Health and Human Services (HHS)

Looking forward to reconnecting with fellow members and senior staff from The White House , Assistant Secretary for Technology Policy , FDA , Office of the Assistant Secretary for Health (OASH) among others at the CancerX Moonshot Summit held this week at U.S. Department of Health and Human Services (HHS) . Make sure to swing by our booth and say hi to our team including Enes Hoşgör, Ph.D. , Marco Smit and Sumir Patel, MD, MBA . Thanks to Moffitt Cancer Center and Digital Medicine Society (DiMe) for putting this together. U.S. Department of Health and Human Services (HHS) will livestream the event here: https://lnkd.in/dVk6iwab VALID AI Coalition for Health AI (CHAI) Decimal.health American Heart Association CB Insights STAT Tracxn HLTH Inc.

Tune in as our CEO, Enes Hoşgör, Ph.D. , is joined by experts from Snowflake , Ada Health and Decimal.health for a panel on the opportunities and challenges posed by the use of GenAI in healthcare!

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Docusaurus

Head of Clinical Affairs

Ray Funahashi

David Shulkin

Bryan Sivak

Enes Hosgor, Ph.D.

CEO & Founder

East Coast Seed Stage Companies With More Than $1M in Revenue

Health Care Companies With Fewer Than 1000 Employees (Top 10K)

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MLOps company currently focused on streamlining clinical validation of AI solutions

CancerX Startup Accelerator

Non Equity Assistance - Gesund

Seed Round - Gesund

500 Emerging Europe

Pre Seed Round - Gesund

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Gesund

Gesund.ai Named to the 2024 CB Insights AI 100 List

Gesund Expands AI Assurance Platform with Trillium Health Partners

Gesund is Proud to Announce International Expansion of its AI Assurance Platform Partner Network With Trillium Health Partners

Gesund.ai Partners with VALID AI and U.S. AI Safety Institute Consortium to Promote Development and Deployment of ...

Funding in AI Startups Sept-1 Issue: ConverSight, Voxel, AI21, and Gesund

‘I need evidence yesterday’: Gesund raises $2 million to provide algorithm-validating data

Gesund.ai offers a service for validating medical AI models against real-world data, including data curation, integration, and analysis.

A platform by Gesund.ai for in-house AI model R&D, allowing organizations to use their own data securely for AI development and validation.

Gesund.ai provides a comprehensive service for conducting independent validation studies necessary for FDA approval of medical AI models.

Supports the entire lifecycle of AI models from development, validation, to post-FDA approval monitoring and revalidation.

A no-code platform designed to facilitate collaboration among data scientists, clinicians, and regulatory professionals.

Gesund.ai's platform is compliant with FDA regulations, ensuring that AI models meet the necessary standards for clinical use.

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