Open-source Machine Learning Platform Launches Healthcare into the Future

Top cardiologist Dr. Amod Amritphale has developed a way to change the future of healthcare and medicine as we know it. He is utilizing artificial intelligence to analyze a large amount of data to accurately predict treatment outcomes and calculate risk in patient profiles of cardiac diseases. The research of Dr. Amritphale, especially the recently published work, will not only further lead physicians, clinicians, and researchers in the field of cardiology but almost every other field of Medicine as they can now follow in his footsteps and follow along the lines of his research to try to improve their own areas of advancement.

Dr. Amritphale feels that the need for the hour is to tackle COVID-19 head on. He believes that opening up all resources for free for the researchers across the world will give an exponential boost to the research capabilities in our unified fight against COVID.  With his vision to establish an open-source, free-for-all platform to guide global researchers, physicians and healthcare workers in the use of Artificial intelligence tools to further their research and support exceptional care of their patients and communities, he co-founded a website This open-source platform with its artificial intelligence tools against COVID and other diseases is proving to be a guiding light across the research and healthcare community with thousands of researchers & physicians (per google analytics) that have already used and benefited from this resource.

What’s different about Dr. Amritphale’s methodology is that not only is he advocating for, treating, and making preventative changes for women and their risk of heart disease, but he is also doing so using computer algorithm programs that he designed. He is also the Director of Cardiovascular Research at the University. “I am involved in extensive research. My focus of research is “Use of Machine learning and Artificial Intelligence in making better decisions in the field of medicine” and I am also using national databases like HCUP. I use this program to develop algorithms that help identify patients who are at increased risk of bad outcomes so that we can preemptively identify them and help them before the worsening of disease processes occur. This helps people live better and live longer and prevents untimely or early death,” Dr. Amritphale says. This method is uniquely his, and he is revolutionizing how people can detect, treat, and determine cardiovascular treatment success with these programs he uses in daily practice.

In regard to treatment outcome prediction, his innovative program actually can reduce patient readmittance after a carotid stent has been placed. The biggest financial issue is the readmittance, a lot of the time there is a financial penalty and the hospital can suffer because of this. His program helps even with cardiology treatments. One of the biggest under-researched issues that cardiology faces is women’s heart health and Dr. Amritphale wants to change that. As the director of the Women’s Heart Program at the University of South Alabama and the University Hospital in Mobile, Alabama, and as an Interventional Cardiologist, he can provide extensive literature for highlighting the issue. “I have taken up the onus to educate women of middle age to teach them the signs of heart disease and preventive methods so that they can seek help before it is too late,” he says.

With various cardiovascular treatments and surgical processes, Dr. Amritphale is able to detect and predict whether or not patients will need to return for an unplanned readmission with his artificial intelligence computer algorithm. From the abstract from his academic study, he and his team of researchers had successful results. “We present a novel deep neural network-based artificial intelligence prediction model to help identify a subgroup of patients undergoing carotid artery stenting who are at risk for short term unplanned readmissions. Prior studies have attempted to develop prediction models but have used mainly logistic regression models and have low prediction ability. The novel model presented in this study boasts 79% capability to accurately predict individuals for unplanned readmissions post carotid artery stenting within 30 days of discharge,” (Amritphale, A., Chatterjee, R., Chatterjee, S. et al. Predictors of 30-Day Unplanned Readmission After Carotid Artery Stenting Using Artificial Intelligence. Adv Ther (2021).

He has even collaborated with researchers from numerous institutions and is guiding them to develop artificial intelligence prediction tools to predict COVID-19 spread. One such work is (Vadyala, S.R., Betgeri, S.N., Sherer, E.A. and Amritphale, A., 2020. Prediction of the number of covid-19 confirmed cases based on k-means-lstm. arXiv preprint arXiv:2006.14752.) where he presented a combination algorithm combining powers of novel tools including Xgboost, K Means, and long short-term memory (LSTM) neural networks to construct a prediction model for COVID-19 cases forecasting in the USA. Women’s heart health, treatment outcome predictions, risk analysis is only the beginning of the innovation that Dr. Amod Amritphale has set out to do. Through educating young doctors in these paramount research methods, he is opening doors to create better healthcare for the future.