Florian Jaeckle
@florianjaeckle.bsky.social
CTO @ Lyzeum Ltd & PostDoc @ Cambridge & Fellow @ Hughes Hall | Developing Interpretable AI for the Diagnosis of Coeliac Disease
Pinned
Very excited to share our paper "Interpretable machine learning-based detection of coeliac disease" published this week in BMJ Digital Health & AI (bmjdigitalhealth.bmj.com/content/1/1/...) @bmj.com.
Key findings below 👇 [1/5]
Key findings below 👇 [1/5]
Reposted by Florian Jaeckle
Another health breakthrough, this time from Cambridge University.
An AI tool can diagnose celiac disease from biopsy images with over 97% accuracy in seconds.
An AI tool can diagnose celiac disease from biopsy images with over 97% accuracy in seconds.
New AI Sees Gluten Damage Doctors Often Miss – And Diagnoses Celiac in Seconds
Cambridge scientists have developed a powerful AI tool that can diagnose celiac disease from biopsy images with over 97% accuracy. Trained on thousands of samples from diverse sources, the algorithm o...
scitechdaily.com
April 14, 2025 at 12:01 PM
Another health breakthrough, this time from Cambridge University.
An AI tool can diagnose celiac disease from biopsy images with over 97% accuracy in seconds.
An AI tool can diagnose celiac disease from biopsy images with over 97% accuracy in seconds.
Very excited to share our paper "Interpretable machine learning-based detection of coeliac disease" published this week in BMJ Digital Health & AI (bmjdigitalhealth.bmj.com/content/1/1/...) @bmj.com.
Key findings below 👇 [1/5]
Key findings below 👇 [1/5]
October 11, 2025 at 9:31 AM
Very excited to share our paper "Interpretable machine learning-based detection of coeliac disease" published this week in BMJ Digital Health & AI (bmjdigitalhealth.bmj.com/content/1/1/...) @bmj.com.
Key findings below 👇 [1/5]
Key findings below 👇 [1/5]
Reposted by Florian Jaeckle
📢 New blog post! Find out how @florianjaeckle.bsky.social based at @campathology.bsky.social @cuh.nhs.uk @hugheshall.bsky.social is using AI to speed up diagnosis of coeliac disease developing an algorithm that correctly identified more than 95 cases out of 100.
Find out more: bit.ly/3Z3Q6C0
Find out more: bit.ly/3Z3Q6C0
May 30, 2025 at 11:59 AM
📢 New blog post! Find out how @florianjaeckle.bsky.social based at @campathology.bsky.social @cuh.nhs.uk @hugheshall.bsky.social is using AI to speed up diagnosis of coeliac disease developing an algorithm that correctly identified more than 95 cases out of 100.
Find out more: bit.ly/3Z3Q6C0
Find out more: bit.ly/3Z3Q6C0
Reposted by Florian Jaeckle
A machine learning model that diagnoses celiac disease from duodenal biopsy images demonstrates strong generalizability across multiple hospitals & has the potential to enhance diagnostic efficiency & reliability in clinical practice. nejm.ai/4iJz7fZ
#AI #MedSky @florianjaeckle.bsky.social
#AI #MedSky @florianjaeckle.bsky.social
May 1, 2025 at 2:10 PM
A machine learning model that diagnoses celiac disease from duodenal biopsy images demonstrates strong generalizability across multiple hospitals & has the potential to enhance diagnostic efficiency & reliability in clinical practice. nejm.ai/4iJz7fZ
#AI #MedSky @florianjaeckle.bsky.social
#AI #MedSky @florianjaeckle.bsky.social
Reposted by Florian Jaeckle
A new #ML model developed for #CeliacDisease diagnosis achieved accuracy, sensitivity, and specificity above 95%, matching or exceeding pathologist-level performance. By diagnosing CD from diverse biopsy samples, it has the potential to reduce diagnostic time and support more reliable diagnoses.
Machine Learning Achieves Pathologist-Level Celiac Disease Diagnosis
The diagnosis of celiac disease (CD), an autoimmune disorder with an estimated global
prevalence of around 1%, generally relies on the histologic examination of duodenal
biopsies. However, interpat...
ai.nejm.org
April 9, 2025 at 1:36 PM
A new #ML model developed for #CeliacDisease diagnosis achieved accuracy, sensitivity, and specificity above 95%, matching or exceeding pathologist-level performance. By diagnosing CD from diverse biopsy samples, it has the potential to reduce diagnostic time and support more reliable diagnoses.
Very excited to share our latest work published yesterday in NEJM AI @ai.nejm.org. We developed an AI model that diagnoses coeliac disease at the same level of accuracy as experienced pathologists.
The paper is available to read here:
ai.nejm.org/stoken/defau...
The paper is available to read here:
ai.nejm.org/stoken/defau...
March 28, 2025 at 3:41 PM
Very excited to share our latest work published yesterday in NEJM AI @ai.nejm.org. We developed an AI model that diagnoses coeliac disease at the same level of accuracy as experienced pathologists.
The paper is available to read here:
ai.nejm.org/stoken/defau...
The paper is available to read here:
ai.nejm.org/stoken/defau...
Reposted by Florian Jaeckle
Exciting developments in this field - congratulations to @florianjaeckle.bsky.social who is co-author of this important research.🌟
Researchers develop AI tool that could speed up coeliac disease diagnosis
Researchers develop AI tool that could speed up coeliac disease diagnosis
Cambridge study finds algorithm is as effective as a pathologist in detecting disease – and much quicker
AI could speed up the diagnosis of coeliac disease, according to research.
Coeliac disease is an autoimmune condition affecting just under 700,000 people in the UK, but getting an accurate diagnosis can take years. Continue reading...
www.theguardian.com
March 28, 2025 at 10:12 AM
Exciting developments in this field - congratulations to @florianjaeckle.bsky.social who is co-author of this important research.🌟
Reposted by Florian Jaeckle
A machine learning model that diagnoses celiac disease from duodenal biopsy images demonstrates strong generalizability across multiple hospitals and has the potential to enhance diagnostic efficiency and reliability in clinical practice. #NEJMAI #OriginalArticle
Machine Learning Achieves Pathologist-Level Celiac Disease Diagnosis
Mar 27, 2025 Original Article by F. Jaeckle and Others
ai.nejm.org
March 27, 2025 at 9:06 PM
A machine learning model that diagnoses celiac disease from duodenal biopsy images demonstrates strong generalizability across multiple hospitals and has the potential to enhance diagnostic efficiency and reliability in clinical practice. #NEJMAI #OriginalArticle
Reposted by Florian Jaeckle
Researchers develop AI tool that could speed up coeliac disease diagnosis
Researchers develop AI tool that could speed up coeliac disease diagnosis
Cambridge study finds algorithm is as effective as a pathologist in detecting disease – and much quicker
AI could speed up the diagnosis of coeliac disease, according to research.
Coeliac disease is an autoimmune condition affecting just under 700,000 people in the UK, but getting an accurate diagnosis can take years. Continue reading...
www.theguardian.com
March 27, 2025 at 1:12 PM
Researchers develop AI tool that could speed up coeliac disease diagnosis
Reposted by Florian Jaeckle
An #AI tool developed by @uniofcam.bsky.social scientists could help accelerate coeliac diagnosis.
"This is the first time AI has been shown to diagnose as accurately as an experienced pathologist whether an individual has coeliac or not" Dr Florian Jaeckle
"This is the first time AI has been shown to diagnose as accurately as an experienced pathologist whether an individual has coeliac or not" Dr Florian Jaeckle
AI is as good as pathologists at diagnosing coeliac disease, study finds - Hughes Hall
A machine learning algorithm developed by Cambridge scientists was able to correctly identify in 97 cases out of 100 whether or not an individual had coeliac disease based on their biopsy, new…
www.hughes.cam.ac.uk
March 27, 2025 at 3:25 PM
An #AI tool developed by @uniofcam.bsky.social scientists could help accelerate coeliac diagnosis.
"This is the first time AI has been shown to diagnose as accurately as an experienced pathologist whether an individual has coeliac or not" Dr Florian Jaeckle
"This is the first time AI has been shown to diagnose as accurately as an experienced pathologist whether an individual has coeliac or not" Dr Florian Jaeckle