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Our work analyzes the artificial intelligence and machine learning (AI/ML) research portfolios of six large research funding organizations from the United States [National Institutes of Health (NIH) and National Science Foundation (NSF)]; Europe [European Commission (EC) and European Research Council (ERC)]; China [National Natural Science Foundation of China (NNSFC)]; and Japan [Japan Society for the Promotion of Science (JSPS)]. The data for this analysis is based on 127,000 research clusters (RCs) that are derived from 1.4 billion citation links between 104.8 million documents from four databases (Dimensions, Microsoft Academic Graph, Web of Science, and the Chinese National Knowledge Infrastructure). Of these RCs, 600 large clusters are associated with AI/ML topics, and 161 of these AI/ML RCs are expected to experience extreme growth between May 2020 and May 2023. Funding acknowledgments (in the corpus of the 104.9 million documents) are used to characterize the overall AI/ML research portfolios of each organization. NNSFC is the largest funder of AI/ML research and disproportionately funds computer vision. The EC, RC, and JSPS focus more efforts on natural language processing and robotics. The NSF and ERC are more focused on fundamental advancement of AI/ML rather than on applications. They are more likely to participate in the RCs that are expected to have extreme growth. NIH funds the largest relative share of general AI/ML research papers (meaning in areas other than computer vision, natural language processing, and robotics). We briefly describe how insights such as these could be applied to portfolio management decision-making., Competing Interests: RK and KB were employed by the company SciTech Strategies, Inc., and assisted this project on a paid contract from CSET. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Rahkovsky, Toney, Boyack, Klavans and Murdick.)

Purpose: Diet-related chronic diseases like diabetes can be dangerous and expensive to treat, especially for patients who do not follow a recommended diet. Meanwhile, prescription drugs can alleviate the symptoms of or control many diet-related chronic diseases, but these drugs may also weaken the resolve to follow recommended diets (moral hazard)., Design: We measure the effect of a diagnosis of chronic disease and subsequent pharmacological treatment on the dietary quality of food purchases using a large panel data set of US consumers. We estimate the effect of prescription drug utilization on food purchases for the following chronic diseases: type 2 diabetes, high cholesterol, heart disease, and obesity., Participants: Panelists of the Information Resources, Inc consumer panel., Measures: Dietary quality is measured as purchases of (1) food groups (ie, fruit, vegetables, and sweets) and (2) nutrients (ie, saturated fat, fiber, sodium, sugar, and total calories)., Analysis: Linear regression with mixed effects on pooled panel (household random effects, city fixed effects)., Results/conclusion: We do not find strong effects of either diagnosis or pharmacological treatment of diet-related disease on food purchases.

Objectives: We estimated the association between the price of healthy and less-healthy food groups and blood sugar among US adults with type 2 diabetes., Methods: We linked 1999-2006 National Health and Nutrition Examination Survey health information to food prices contained in the Quarterly Food-at-Home Price Database. We regressed blood sugar levels on food prices from the previous calendar quarter, controlling for market region and a range of other covariates. We also examined whether the association between food prices and blood sugar varies among different income groups., Results: The prices of produce and low-fat dairy foods were associated with blood sugar levels of people with type 2 diabetes. Specifically, higher prices for produce and low-fat dairy foods were associated with higher levels of glycated hemoglobin and fasting plasma glucose 3 months later. Food prices had a greater association with blood sugar for low-income people than for higher-income people, and in the expected direction., Conclusions: Higher prices of healthy foods were associated with increased blood sugar among people with type 2 diabetes. The association was especially pronounced among low-income people with type 2 diabetes.

Cardiovascular diseases (CVD) cost Americans billions of dollars per year. High cholesterol levels, which are closely related to dietary habits, are a major contributor to CVD. In this article, we study whether changes in food prices are related to cholesterol levels and whether taxes or subsidies on particular foods would be effective in lowering cholesterol levels and, consequently, CVD costs. We find that prices of vegetables, processed foods, whole milk and whole grains are significantly associated with blood cholesterol levels. Having analyzed the costs and benefits of government interventions, we find that a subsidy of vegetables and whole grains would be an efficient way to reduce CVD expenditures., (Published by Elsevier B.V.)