New Technology in Diagnosing Respiratory Diseases

The article under the headline “These Algorithms Could Bring an End to the World’s Deadliest Killer” was written by Apoorva Mandavilli and published in The New York Times on the 20th of November 2020. The article is dedicated to an app called qXR which is currently being used in rural India to scan X-rays in order to detect signs of tuberculosis and other respiratory diseases. The need for such aid is caused by the lack of experts in radiology.

It is emphasized in the article that, although the app is helpful for the diagnosis of tuberculosis, it cannot be a proper replacement for a human. However, the joint effort of a technology and a clinician proves to be accurate and valuable in the medical field (Mandavilli, 2020). Furthermore, it is highlighted that the algorithms can potentially detect not only a fully developed disease but also the subtle signs of various conditions, including Covid-19 (Mandavilli, 2020). Finally, it is stressed that the app can be used for routine examinations for people at risk of contracting a dangerous respiratory disease (Mandavilli, 2020). Therefore, qXR offers a number of ways in which it can be utilized.

Even though this technology was initially developed as a means of aid for hospitals and regions lacking professional radiologists, it can be extremely useful for the healthcare in our country. The opportunity to scan X-rays for the obvious and subtle signs of a disease with the help of an app allows clinicians to detect conditions promptly. An early diagnosis leaves more time for the actual treatment, substantially increasing the chances of recovery.

Furthermore, these technologies can be used as a means of preventing a disease. The app can detect signs of a potential threat before it has started to develop. Therefore, regular screenings of patients with conditions which make them susceptible to lung illnesses can be done more quickly and accurately with the help of qXR. Thus, such algorithms can be helpful to clinicians with various levels of training in different regions all over the world.

Reference

Mandavilli, A. (2020). These algorithms could bring an end to the world’s deadliest killer. The New York Times. Web.

Cite this paper

Select style

Reference

StudyCorgi. (2022, March 4). New Technology in Diagnosing Respiratory Diseases. https://studycorgi.com/new-technology-in-diagnosing-respiratory-diseases/

Work Cited

"New Technology in Diagnosing Respiratory Diseases." StudyCorgi, 4 Mar. 2022, studycorgi.com/new-technology-in-diagnosing-respiratory-diseases/.

* Hyperlink the URL after pasting it to your document

References

StudyCorgi. (2022) 'New Technology in Diagnosing Respiratory Diseases'. 4 March.

1. StudyCorgi. "New Technology in Diagnosing Respiratory Diseases." March 4, 2022. https://studycorgi.com/new-technology-in-diagnosing-respiratory-diseases/.


Bibliography


StudyCorgi. "New Technology in Diagnosing Respiratory Diseases." March 4, 2022. https://studycorgi.com/new-technology-in-diagnosing-respiratory-diseases/.

References

StudyCorgi. 2022. "New Technology in Diagnosing Respiratory Diseases." March 4, 2022. https://studycorgi.com/new-technology-in-diagnosing-respiratory-diseases/.

This paper, “New Technology in Diagnosing Respiratory Diseases”, was written and voluntary submitted to our free essay database by a straight-A student. Please ensure you properly reference the paper if you're using it to write your assignment.

Before publication, the StudyCorgi editorial team proofread and checked the paper to make sure it meets the highest standards in terms of grammar, punctuation, style, fact accuracy, copyright issues, and inclusive language. Last updated: .

If you are the author of this paper and no longer wish to have it published on StudyCorgi, request the removal. Please use the “Donate your paper” form to submit an essay.