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AI vs. Humans: AI Solution Beats Stanford Radiologists in Chest X-ray Diagnostics Competition

by Jasmine Pennic 08/22/2019 Leave a Comment

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AI vs. Humans: AI Solution Beats Stanford Radiologists in Chest X-ray Diagnostics Competition

JF Healthcare, a Nanchang, China-based medical diagnostic startup is the first organization in the world to beat Stanford University radiologists in a competition designed by the Stanford Machine Learning group to compare the capability of artificial intelligence (AI) to human experts in interpreting chest x-rays.

Standard Chest X-ray Diagnostic Competition Results

AI vs. Humans: AI Solution Beats Stanford Radiologists in Chest X-ray Diagnostics Competition

The AI team from JF Healthcare recently achieved an average AUC score (a measure of diagnostic accuracy) of 0.926 and is currently ranked No. 1 in the world on Stanford’s CheXpert leaderboard. Significantly, the JF team outperforms all three Stanford radiologists on the test set, demonstrating the role that AI can play in providing precise medical diagnostics, especially in underserved areas of the world, with profound implications for the treatment of lung cancer, tuberculosis and other diseases of the thorax.

JF Healthcare Background

Founded in 2015 by former Siemens healthcare executive Frank Wu, JF offers remote diagnostic services, focusing on chest x-rays, for rural township hospitals in China where certified radiologists are often not available.  Its mobile screening truck is expected to screen more than ten provinces in China for tuberculosis by the end of 2019, offering a half-million people the possibility of early detection while preventing the spread of disease to broader populations.

JF plans to develop a chest x-ray screening product to simultaneously screen for tuberculosis, lung cancer, and pneumonia, covering the major thorax diseases based on more than 300,000 chest x-ray images with curated radiology reports collected from approximately 1,000 township hospitals. The team is hoping to fully leverage the clinical value of chest x-rays through AI and deliver it to the massive township hospital patient population in China where radiologists are most needed.

Why It Matters

“The goal is to be better than the best human in making diagnoses and deliver low-cost care with a level of quality that is equivalent to the best hospitals in the world. To do that, the secret is not math; it’s a huge volume of well-curated data,” said Wu, JF Healthcare’s Founder and CEO. “There are 3 billion people in the world without access to quality healthcare. The first step in remedying this problem is providing extremely accurate diagnostics, which is at the core of our strategy and mission.”

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Tagged With: AI, Artificial Intelligence, cancer, lung, Lung Cancer, Machine Learning, patient population, pneumonia, Radiologist, radiology, Siemens, Stanford Health Care

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