The words “artificial intelligence” are often paired with headlines warning against its dangers, but as AI and machine learning continue to improve, they may save your life or the life of someone you care about.
While the use of artificial intelligence in healthcare is relatively new, ongoing research has yielded promising results and led to technological innovations that are already proving successful. Take, for instance, the trusty stethoscope. That simple instrument has been helping doctors diagnose patients since 1816, but now it’s getting the AI treatment.
But first, let’s examine the importance of auscultation, the method of listening to internal body sounds, in medicine over the centuries.
Ancient Egyptian medical papyrus from the 17th century BCE refer to audible signs of disease in the body. Over 2,000 years ago, in ancient Greece, the Father of Medicine himself, Hippocrates, described a method of shaking a patient by the shoulders and listening for sounds coming from the chest. Hippocrates would also put his ear directly against the chest to listen for fluid.
In the 1700s, an Austrian physician named Leopold Auenbrugger formally added a percussion technique to the diagnosis process. Inspired by his father’s method of tapping wine casks in his hotel cellar to check their levels, Auenbrugger found that, with his ear pressed against the chest, he could tap lightly on a patient’s chest and hear tonal changes that indicate tissue and organ density. He published his findings, but the technique was largely ignored until the 1800s, when Napoléon Bonaparte’s favourite physician, Jean-Nicolas Corvisart, brought it to prominence. In 1808, Corvisart translated Auenbrugger’s booklet from Latin to French. One of Corvisart’s students was a man named René Laennec, who would go on to invent the stethoscope.
In 1816, Laennec had a young female patient “laboring under general symptoms of diseased heart, and in whose case percussion and the application of the hand were of little avail on account of the great degree of fatness.” Laennec writes in his De l’Auscultation Médiate (Treatise on Medical Auscultation) that he remembered how sound travels along a solid object, such as hearing “the scratch of a pin at one end of a piece of wood on applying our ear to the other.” Laennec rolled pieces of paper into a tube and put one end to the woman’s chest and the other to his ear. Not only could he hear the woman’s heart, but the sound was more clear and distinct than any direct ear-to-chest contact.
Laennec was likely also inspired by his pastime of playing the flute and woodturning to create his instruments. With this knowledge, the gifted physician created a hollow wood cylinder with a funnel-shaped cone at one end and a listening hole at the other. A plug was inserted into the funnel to listen to the heart and removed when listening to the lungs.
Stethoscope technology has continued to improve ever since, from the invention of binaural (two-ear) listening to advancements in materials and external noise reduction. The latest iterations have seen the introduction of artificial intelligence to aid physicians in diagnosing illness and disease.
AI stethoscopes typically feature a built-in electrocardiogram (ECG). Through the artificial intelligence software, the device analyzes the ECG reading and helps identify atrial fibrillation and heart murmurs that may indicate heart failure. In one study, the AI stethoscope correctly identified heart failure 9 out of 10 times. The stethoscope missed few cases, and, equally as important, there were few false positives. With the testing method used, the AI stethoscope outperformed other studies that used a standard ECG.
In another study of artificial intelligence stethoscopes, AI showed a twofold improvement over primary care physicians in detecting audible valvular heart disease (VHD). The algorithm had a 94.1 percent sensitivity for VHD compared to the doctors’ 41.2 percent accuracy.
As more primary care physicians adopt modern AI stethoscopes, the rates of early detection of heart failure are likely to increase while also reducing unnecessary referrals to specialists. Traditional stethoscopes are also used to diagnose and monitor other areas of the body, such as the abdomen. In time, we may see artificial intelligence expand to cover these use cases, too. All of which means better health outcomes for patients like you and me.
Our thanks to the Twenty Thousand Hertz podcast for inspiring this article. Listen to examples of stethoscope technology in their “Sonic Diagnosis” episode.
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FAQs
How much do AI stethoscopes cost, and are they accessible to all healthcare providers?
AI stethoscopes can vary widely in cost, and this can influence how accessible they are to different healthcare providers. Prices can range from a few hundred to several thousand dollars, depending on the sophistication of the device and the software it uses. For some smaller clinics or healthcare providers with limited budgets, the cost may be prohibitive, potentially slowing down widespread adoption. However, as the technology advances and becomes more common, prices may decrease, making AI stethoscopes more accessible over time.
Are there any risks or limitations associated with using AI stethoscopes compared to traditional methods?
There are indeed some risks and limitations associated with using AI stethoscopes compared to traditional methods. While AI can significantly improve diagnostic accuracy, it is not infallible. There might be concerns about over-reliance on technology, especially if the AI’s algorithms are not fully transparent or if they do not perform equally well across diverse patient populations. Additionally, like any electronic device, AI stethoscopes could be prone to technical malfunctions or errors, which could potentially lead to missed diagnoses or incorrect interpretations if not carefully monitored by trained professionals.
How does the integration of AI in stethoscopes affect the role of doctors and their decision-making process?
The integration of AI in stethoscopes has a profound impact on the role of doctors and their decision-making processes. While AI can enhance a physician’s ability to detect certain conditions, it doesn’t replace the need for clinical judgment. Doctors must still interpret AI-generated data within the broader context of a patient’s health, symptoms, and history. This new technology can complement a doctor’s expertise, allowing for more accurate and timely diagnoses, but it also requires that physicians adapt to new tools and learn to integrate them effectively into their practice. This dynamic can potentially shift the way healthcare is delivered, emphasizing the importance of collaboration between human expertise and advanced technology.