AI Heart Surgery: Artificial Intelligence (AI) are currently undergoing surgical procedures assisted by Artificial Intelligence (AI) in numerous countries across the globe. This marks a significant departure from traditional surgical methods, as the entire operation can now be conducted solely by a doctor without the need for a large medical team. This innovative technique not only reduces the time required for bypass surgery but also minimizes incisions during the procedure. Additionally, the associated risks are substantially lower when compared to conventional surgical approaches.
Let us know from experts how heart surgery was done before AI technology and how different AI is from that now.
A groundbreaking study involving cardiologists from three major US hospitals has shown that artificial intelligence (AI) can significantly improve predictions of patient survival after heart surgery.
Gathering information from nearly 46,000 patients across three major U.S. healthcare systems—Cedars-Sinai, Stanford University, and Columbia University—the researchers fed the ECG data into the advanced AI model. The results were impressive, with the AI algorithm exhibiting an 83% accuracy rate in predicting patient survival 30 days post-heart surgery, outperforming the standard method known as the Revised Cardiac Risk Index, which achieved a 67% accuracy.
Dr. Da Ouyang, a co-author of the study and a cardiologist at the Smidt Heart Institute at Cedars-Sinai in Los Angeles, said that the AI’s precision in estimating surgical risks plays a crucial role in informing the decision-making process around whether to proceed with surgery.
The study drew from ECG data of patients treated at three prominent U.S. healthcare systems: Cedars-Sinai, Stanford University, and Columbia University. Electrocardiograms measure the heart’s electrical activity and function.
Patients identified as high-risk by the AI based on their pre-surgery ECGs had a staggering nine-fold increased risk of mortality within the first month after their surgery, according to findings by Ouyang and colleagues.
Recognizing the limitations of current clinical risk prediction tools, Dr. Ouyang highlighted Patients whose pre-op ECGS helped AI identify them as being high-risk had a nine-fold increased risk of dying in the month after their surgery,
“Current clinical risk prediction tools are insufficient,” he noted in a Cedars-Sinai news release. “This AI model could potentially be used to determine exactly which patients should undergo an intervention and which patients might be too sick.”
However, its trend has increased significantly in countries like America, Britain and Germany. There is less risk of any mistake in this surgery and the patient also recovers quickly. Normal bypass surgery takes seven to eight hours to perform, but with the help of AI it can be done in much less time. With AI the operation is quite precise. A smaller incision is made than normal surgery.
Looking ahead, the researchers are exploring the possibility of uploading the AI technology to the internet, making it easily accessible to doctors and patients worldwide. The study’s findings were recently published in The Lancet Digital Health journal, showcasing the promising synergy between historical medical data and contemporary AI capabilities.