Top physician-researcher Dr. Amod Amritphale is making waves with machine learning A.I. to advance medicine in ways that weren’t thought possible. As a cardiologist, researcher, program director, and teacher, his innovation doesn’t stop and neither does he. 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-19. 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 https://www.rxpredictions.com/. 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.
He has 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 https://arxiv.org/abs/2006.14752 (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.
In addition to researching prediction tools against COVID-19, he has taken an onus to educate the doctors of the future. “I take so much pride in teaching budding cardiologists, Internal Medicine physicians, and medical students, and at any time I am teaching at least six budding cardiologists of tomorrow. I inculcate in them the best practices, ethics, and guidelines that they should follow when they start seeing patients in the community,” Dr. Amritphale says, smiling. “These students are being trained in not just traditional practices of medicine but also advanced research methods.” His advanced research methods provide a way for people with heart conditions or health issues to have their data analyzed in a way that would make it easier to determine and predict patient outcomes. One of the biggest issues faced in cardiology is women’s heart health.
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.
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). https://doi.org/10.1007/s12325-021-01709-7).
Through his advancements in Artificial Intelligence, he is helping world researchers understand and predict the spread of COVID-19. The philanthropic efforts of Dr. Amritphale, wherein he has opened all his research as an open-platform free-for-all model that is being used by thousands of world researchers and is proving to be a guiding light and a ray of hope in these times of COVID turmoil.