Mecha Health

Foundation models to automate x-ray analysis for radiologists

W25

Active

artificial-intelligence

https://www.mecha-health.ai/

Foundation models to automate x-ray analysis for radiologists

Mecha Health builds foundation models to automate x-ray analysis for radiologists. We take medical images and process them using proprietary models to produce accurate draft medical reports. Our first model was built in less than two months, and beat Microsoft, Google, and OpenAI on clinical accuracy metrics. On top of that, it’s two orders of magnitude smaller and trained with a quarter of the data. We are partnering with the largest privately owned radiology practice in the US and a multinational tele-radiology company to provide them with their own foundation model, enabling their radiologists to go from reading 1 scan per hour to 1 scan every 5 minutes. By charging on a per scan basis, x-ray report generation represents a 40B+ market opportunity.

Mecha Health

Founded:2024

Team Size:4

Status:

Active

Location:San Francisco

Group Partner:Michael Seibel

Active Founders

Ahmed Abdulaal, Founder

Medical doctor @Imperial, where I gained entry to the most competitive deanery in the country. Microsoft PhD scholar in machine learning @UCL - I have more than 20 peer reviewed publications in medicine, digital healthcare, and machine learning - including first author publications in top AI venues such as ICLR. 360+ citations on google scholar. Ex Research Scientist at the Center for Artificial Intelligence @AstraZeneca. Building the future of automated radiology @Mecha Health.

Ahmed Abdulaal

Mecha Health

Hugo Fry, Founder

Mathematics (BA) and Physics (MSc) graduate from the University of Cambridge, ranking top 30 in the university. British Physics Olympiad participant, ranking in the top 11 in the UK. Former ML interpretability research scholar (MATS), where I was the first in the world to use Sparse Autoencoders on vision models. My research has been cited by Anthropic and Google DeepMind. Currently working on building state of the art radiology report generation AI in a way that is interpretable and safe.

Hugo Fry

Mecha Health

Ayodeji Ijishakin, Founder

I am a Machine Learning & Medical Imaging PhD candidate from University College London (UCL). During my PhD I published work at tier-one Machine Learning venues (NeurIPS, ICML & ICLR), and was invited to present my work at international medical imaging conferences, Digitas, & Harvard Medical School. Before this startup I was poached by my Professors from UCL including the Head of Computer Science to be CEO for their spin-out. Currently building Radiology 3.0 by Automating reporting.

Ayodeji Ijishakin

Mecha Health

Nina Montaña Brown, Founder

ex-ML Engineer across multiple medical device startups, with experience in FDA and CE marked medical devices, as well as LLM safety in healthcare. My PhD in Medical Imaging (UCL) focussed on surgical vision; my work has been patented, cited 100+ times, and published across the world's highest impact scientific venues (NeurIPS, ICLR). Currently building safe and interpretable radiology automations for the future @Mecha Health

Nina Montaña Brown

Mecha Health

Company Launches

Mecha Health 🩻 Trustworthy medical image reporting using AI

See original launch post ›

TLDR;
Mecha Health helps radiologists save time and effort by producing draft reports of medical images using AI.

The Problem: Too Many Scans Not Enough Doctors.
Due to a shortage of experts, US radiologists have to read 100 - 250+ studies per day, and this means that 55% have reported high levels of burnout. Additionally, patients sometimes have to wait days to receive medical reports for their scans due to backlogs. At times, this can result in preventable patient harm.

Our Solution: Accurate & Interpretable Medical Image Analysis.
We improve the reporting process by producing draft reports with AI and have invented new science to do this both accurately and safely. Our system can trace every finding to its visual source in the image and evidence each finding with examples from the training dataset. This allows for transparent reporting that doctors can trust.

Our Background: Frontier Scientific Expertise.
We are leading researchers in machine learning and medical imaging having published in tier-one AI venues (NeurIPS, ICLR, ICML). Nina, Ahmed & Deji crossed paths through University College London’s Medical Imaging PhD program. Hugo met the team after he published AI research that was cited by Anthropic. Ahmed, a trained medical doctor from Imperial College London, witnessed firsthand how reporting delays harm patient outcomes—driving Mecha Health’s mission to transform radiology.

Our Ask: Intros to Pioneering Medical Professionals and Healthcare Executives.
Please reach out to the team at ahmed@mecha-health.ai if you know any tech-forward clinicians, radiologists, radiology practices, or healthcare executives who could benefit from our technology. You can also check us out at https://mecha-health.ai/.

Watch our full product video here
https://youtu.be/s5uJS7S8EF4