AI finds a way to people's hearts (literally!)
Unveiling a groundbreaking and accurate AI-based method to classify
cardiac function and disease using chest X-Rays

Date:
July 6, 2023
Source:
Osaka Metropolitan University
Summary:
Scientists have successfully developed a model that utilizes
AI to accurately classify cardiac functions and valvular heart
diseases from chest radiographs. The Area Under the Curve, or AUC,
of the AI classification showed a high level of accuracy, exceeding
0.85 for almost all indicators and reaching 0.92 for detecting
left ventricular ejection fraction -- an important measure for
monitoring cardiac function.


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FULL STORY ==========================================================================
AI (artificial intelligence) may sound like a cold robotic system, but
Osaka Metropolitan University scientists have shown that it can deliver heartwarming -- or, more to the point, "heart-warning" -- support. They unveiled an innovative use of AI that classifies cardiac functions
and pinpoints valvular heart disease with unprecedented accuracy,
demonstrating continued progress in merging the fields of medicine and technology to advance patient care. The results will be published in
The Lancet Digital Health.

Valvular heart disease, one cause of heart failure, is often
diagnosed using echocardiography. This technique, however, requires
specialized skills, so there is a corresponding shortage of qualified technicians. Meanwhile, chest radiography is one of the most common tests
to identify diseases, primarily of the lungs. Even though the heart is
also visible in chest radiographs, little was known heretofore about the ability of chest radiographs to detect cardiac function or disease. Chest radiographs, or chest X-Rays, are performed in many hospitals and very
little time is required to conduct them, making them highly accessible
and reproducible. Accordingly, the research team led by Dr. Daiju Ueda,
from the Department of Diagnostic and Interventional Radiology at the
Graduate School of Medicine of Osaka Metropolitan University, reckoned
that if cardiac function and disease could be determined from chest radiographs, this test could serve as a supplement to echocardiography.

Dr. Ueda's team successfully developed a model that utilizes AI to
accurately classify cardiac functions and valvular heart diseases from
chest radiographs.

Since AI trained on a single dataset faces potential bias, leading to
low accuracy, the team aimed for multi-institutional data. Accordingly,
a total of 22,551 chest radiographs associated with 22,551 echocardiograms
were collected from 16,946 patients at four facilities between 2013 and
2021. With the chest radiographs set as input data and the echocardiograms
set as output data, the AI model was trained to learn features connecting
both datasets.

The AI model was able to categorize precisely six selected types of
valvular heart disease, with the Area Under the Curve, or AUC, ranging
from 0.83 to 0.92. (AUC is a rating index that indicates the capability of
an AI model and uses a value range from 0 to 1, with the closer to 1, the better.) The AUC was 0.92 at a 40% cut-off for detecting left ventricular ejection fraction -- an important measure for monitoring cardiac function.

"It took us a very long time to get to these results, but I believe this
is significant research," stated Dr. Ueda. "In addition to improving
the efficiency of doctors' diagnoses, the system might also be used
in areas where there are no specialists, in night-time emergencies,
and for patients who have difficulty undergoing echocardiography."
* RELATED_TOPICS
o Health_&_Medicine
# Heart_Disease # Mesothelioma # Stroke_Prevention #
Diseases_and_Conditions
o Computers_&_Math
# Computer_Modeling # Mathematical_Modeling # Mathematics
# Information_Technology
* RELATED_TERMS
o Defibrillation o Artificial_heart o CPR o Electrocardiogram
o Heart_failure o Heart o Heart_rate o South_Beach_diet

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========================================================================== Journal Reference:
1. Daiju Ueda et al. Artificial intelligence-based model to classify
cardiac
functions from chest radiographs: a multi-institutional,
retrospective model development and validation study. The Lancet
Digital Health, 2023 DOI: 10.1016/S2589-7500(23)00107-3 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2023/07/230706190150.htm

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