AI Detects Fatty Liver Disease in X-rays
- A new artificial intelligence model can detect fatty liver disease using standard chest X-rays, according to researchers at Osaka Metropolitan University's Graduate School of Medicine.
- If untreated, fatty liver disease can progress to cirrhosis or liver cancer.
- Associate Professor Sawako Uchida-Kobayashi and Associate Professor Daiju Ueda led the research team that developed the AI model.
AI is revolutionizing healthcare. A groundbreaking new AI model can now detect fatty liver disease using readily available chest X-rays. This innovative approach, developed by researchers at Osaka Metropolitan university, presents a possibly more accessible and affordable method for identifying a condition affecting millions globally. The AI model analyzes chest X-rays, a significant advancement over costly methods like ultrasounds and MRIs. Accuracy is high, boasting an AUC range of 0.82 to 0.83, proving that this innovative use of AI is making strides. This news, reported in News Directory 3, could lead to an earlier diagnosis. The team hopes to refine the model for wider clinical use and better patient outcomes, making the detection and treatment of fatty liver disease more efficient. Discover whatS next?
AI Model Spots Fatty Liver Disease in Chest X-Rays
A new artificial intelligence model can detect fatty liver disease using standard chest X-rays, according to researchers at Osaka Metropolitan University‘s Graduate School of Medicine. The AI offers a potentially cheaper and more accessible method for early detection of the condition, which affects an estimated 25% of people globally.
If untreated, fatty liver disease can progress to cirrhosis or liver cancer. Current diagnostic methods, such as ultrasounds, CT scans, and MRIs, often require specialized equipment and can be costly. Chest X-rays, while typically used for lung and heart examinations, also capture images of the liver.
Associate Professor Sawako Uchida-Kobayashi and Associate Professor Daiju Ueda led the research team that developed the AI model. They trained the system using 6,599 chest X-ray images from 4,414 patients, incorporating controlled attenuation parameter (CAP) scores.
The AI model demonstrated high accuracy,with the area under the receiver operating characteristic curve (AUC) ranging from 0.82 to 0.83.
“The progress of diagnostic methods using easily obtainable and inexpensive chest X-rays has the potential to improve fatty liver detection. We hope it can be put into practical use in the future,” professor Uchida-Kobayashi said.
what’s next
The researchers hope to refine the AI model for broader clinical submission,potentially leading to earlier diagnosis and treatment of fatty liver disease.