Detecting COVID-19 with Artificial Intelligence, Imaging Technology

Using artificial intelligence technology, Terasaki Institute for Biomedical Innovation (TIBI) researchers developed and validated an image-based detection model for COVID-19. The model analyzes lung images and can detect COVID-19 infection.

Medical imaging has become an important tool in the diagnosis and prognostic assessments of diseases. In recent years, artificial intelligence models have been implemented with imaging technology to improve diagnostic capabilities. In comporting AI into imaging technology, models can reveal disease characteristics that are not visible to the naked eye.

With the pandemic continuing to spread, there has been a high demand for rapid and accurate methods of COVID-19 infection detection. The current primary method has been using reverse transcription-polymerase chain reaction (RT-PCR) on samples collected from nasal or throat swabs.

However, this method can lead to inaccuracies due to sampling errors, low viral load, and sensitivity limitations. Inaccuracies are especially significant for patients in the early stages of infection.

In a multi-institute collaborative effort, TIBI researchers created an AI image-based detection model to identify COVID-19 infection. Researchers used a model to automatically collect imaging data from the lung lobes. The Researchers then analyzed data was then analyzed to identify features as potential diagnostic biomarkers for COVID-19.

In the artificial intelligence model, the diagnostic biomarkers were used toenabled researchers to differentiate COVID-19 patients from pneumonia and healthy patients. The model was developed using a cohort of 704 chest x-rays and validated with 1597 cases from multiple sources made up of healthy, pneumonia, and COVID-19 patients. The results indicated the model was successful in classifying diagnoses of various patients.

“This highly advanced artificial intelligence model further helps our ability to precisely detect COVID-19 patients. In addition, such a model can be applied for diagnosis of other diseases using different imaging modalities,” lead researcher Samad Ahadian, PhD, said in a press release.

According to the study, using computer modeling with data extracted from medical images shows promise in improving precision medicine and could revolutionize medical practice in clinics. Additionally, creating methodologies to capture full sets of information while suppressing irrelevant features will enhance the reliability of artificial intelligence models.

The proposed approach is to apply AI models into precision medicine to provide an efficient, inexpensive, and non-invasive method to strengthen the diagnostic abilities of imaging.

“Artificial intelligence-driven models with diagnostic and predictive capabilities are a powerful tool that are an important part of our research platforms here at the institute,” said TIBI CEO and Director Ali Khademhosseini, PhD, Director and CEO of TIBI. “This will carry over into countless applications in the biomedical field and in the clinic.”