Medtronic has announced that it will acquire long-time partner Nutrino, an AI powered personalized nutrition platform for an undisclosed sum. As part of the deal Medtronic will be integrating Nutrino's AI-driven personalized insights and food database. The acquisition is set to specifically boost Medtronic's offerings for people living with diabetes and offer the company's predictive glycemic response algorithm, which will be integrated with Medtronic's CGM system. "Bringing Nutrino and their nutrition-related expertise into our organization will give us a substantial differentiator in the diabetes industry and accelerate our progress to help people with diabetes live with greater freedom and better health," Hooman Hakami, executive vice president and president of the Diabetes Group at Medtronic, said in a statement. "The Nutrino team has been an outstanding partner over the past few years. We are excited to welcome them to our team, and I have no doubt that, together, we will make a profound impact on the lives of people with diabetes."
Edwards Lifesciences is delving deeper into the realm of artificial intelligence through a partnership with San Francisco-based Bay Labs. The goal of the collaboration, which has multiple initiatives is to improve the detection of heart disease. Some of the initiatives include, the development of new AI-powered algorithms in Bay Labs' EchoMD measurement and interpretation software suite; support for ongoing clinical studies at institutions; and the integration of EchoMD algorithms into Edwards Lifesciences' CardioCare quality care navigation platform. Irvine, CA-based Edwards' CardioCare program combines clinical consulting expertise with a cloud-based platform to facilitate in the identification, referral, and care pathway management of patients with structural heart disease. CardioCare can help hospitals improve quality by reducing variability in echocardiography and ensure effective communication between care settings to ensure patients access to care.
New mobile app from Medtronic, Sugar.IQ, applies AI technology from IBM Watson Health to help people with diabetes make more informed decisions. Self-driving cars may not be here yet, but artificial intelligence is being used today to help patients with diabetes to manage their glucose. IBM announced its advancement in using artificial intelligence (AI), machine learning, and analytic technologies to address the data-driven obstacles of diabetes, as presented at the American Diabetes Association's (ADA) 78th Scientific Sessions. Through IBM Watson Health's ongoing partnership with Medtronic, the companies announced the commercial availability of Sugar.IQ with Watson, an app that aims to give people insights to help manage their diabetes. They also announced findings from three data presentations at ADA, including real-world data underscoring the value of machine learning and analytic tools in diabetes.
Medtronic's mission is to alleviate pain, restore health, and extend life through the application of biomedical engineering, explains Elaine Gee, PhD, Senior Principal Algorithm Engineer specializing in Artificial Intelligence at Medtronic. It's a mission Gee is well equipped for. With over 15 years' experience in modeling, bioinformatics, and engineering, she drives machine learning algorithm development and analytics to support next-generation medical devices for diabetes management. On behalf of AI Trends, Ben Lakin, from Cambridge Innovation Institute, sat down with Gee to discuss her most recent focus: algorithm development related to glucose sensing to improve the accuracy and performance of continuous glucose monitoring devices, also known as CGMs. Editor's Note: Gee will be giving a featured presentation on Advancing Continuous Glucose Monitoring Sensor Development with Machine Learning at Sensors Summit in San Diego, December 10-12.
For decades, dietary advice was based on the premise that high intakes of fat cause obesity, diabetes, heart disease, and possibly cancer. Recently, evidence for the adverse metabolic effects of processed carbohydrate has led to a resurgence in interest in lower-carbohydrate and ketogenic diets with high fat content. However, some argue that the relative quantity of dietary fat and carbohydrate has little relevance to health and that focus should instead be placed on which particular fat or carbohydrate sources are consumed. This review, by nutrition scientists with widely varying perspectives, summarizes existing evidence to identify areas of broad consensus amid ongoing controversy regarding macronutrients and chronic disease. A report by the U.S. Senate Select Committee on Nutrition and Human Needs in 1977 called on Americans to reduce consumption of total and saturated fat, increase carbohydrate intake, and lower calorie intake, among other dietary goals (1). This report, by elected members of Congress with little scientific training, was written against a backdrop of growing public concern about diet-related chronic disease, precipitated in part by attention surrounding President Eisenhower's heart attack in 1955. Even then, the recommendations were hotly debated. The American Medical Association stated that "The evidence for assuming benefits to be derived from the adoption of such universal dietary goals as set forth in the report is not conclusive … [with] potential for harmful effects." Indeed, the lack of scientific consensus was reflected in the voluminous, 869-page "Supplemental Views" published contemporaneously by the committee. Nonetheless, reduction in fat consumption soon became a central principle of dietary guidelines from the U.S. government and virtually all nutrition- and health-related professional organizations. The Surgeon General's Report on Nutrition and Health in 1988 identified reduction of fat consumption as the "primary dietary priority," with sugar consumption only a secondary concern for children at risk for dental caries (3).