AI for a Cost-Effective Heart Disease Detector
By MedTech Outlook | Tuesday, March 05, 2019
Artificial intelligence (AI) has gripped every sector, but in the healthcare, it is receiving an extravagant promotion with its capacity of fetching information, processing it and concluding it without any direct inputs by a human. This intelligent technology is able to process healthcare functions faster without any errors. The technology in the healthcare industry is used to analyze diseases, treatments techniques, and outcome of patients. The solutions provided by advanced AI-powered technologies eliminate tedious tasks, mitigate risks, and improve the efficiency of the chain of the process. AI-based technology learns and grows similar to humans, but the data processing and storage capacity of this is virtually unlimited.
The advancements and innovations each day in AI are changing the scenario of the healthcare industry from diagnosing disease to the prediction of treatment. In past months, a number of studies reveal how AI is revolutionizing the detection of diseases including genetic disorders, cancers, and Alzheimer’s. Recently, researchers at the Imperial College London and the University of Melbourne have created an artificial intelligence software, which was able to predict the prognosis of patients with ovarian cancer more accurately than current methods. Following the diagnosis, it can also predict what treatment would be most effective for patients.
The application of artificial intelligence (AI) to electrocardiogram (EKG) which is a widely available, inexpensive test leads to a simple, affordable early indicator of a heart failure precursor. According to the research report published by Nature Medicine, the test accuracy of the AI/EKG system when compared to other standard screening tests such as breast cancer mammography shows positive results.
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According to a report by timesnownews.com, researchers from Mayo Clinic in the U.S. have found that measuring natriuretic peptide levels (BNP) is the best existing screening test for asymptomatic left ventricular dysfunction, a disorder that is treatable and is characterized by the presence of a weak heart pump with a risk of overt heart failure. The conclusion of the study against the hypothesis that asymptomatic left ventricular dysfunction could be reliably detected in the EKG by a properly trained neural network is proved right. Artificial intelligence will continue to advance and transform the ways of delivering healthcare services and improving patient outcomes.