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Introduction
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Publications
Publications (67)
The purpose of this study was to: (1) compare the relative efficacy of different combinations of three behavioral intervention strategies (i.e., personalized reminders, financial incentives, and anchoring) for establishing physical activity habits using an mHealth app and (2) to examine the effects of these different combined interventions on intri...
Background
Clinical decision support systems have been widely deployed to guide healthcare decisions on patient diagnosis, treatment choices, and patient management through evidence-based recommendations. These recommendations are typically derived from clinical practice guidelines created by clinical specialties or healthcare organizations. Althou...
Background:
Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD.
Objective:
The aim is to examine patient enga...
BACKGROUND
Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD.
OBJECTIVE
The aim is to examine patient engageme...
The growing availability of data from electronic health records (EHRs), digitized claims, and patient-provider communications is providing opportunities to understand and improve primary care and patient engagement. Computational tools such as artificial intelligence (AI), machine learning (ML), analytics, and visualization are providing novel, dat...
Despite recent advances in digital health solutions and machine learning, personal health applications that aim to modify health behaviors are still limited in their ability to offer more personalized decision support. Moreover, while many personal health applications cater to general health and well-being, there remains a significant opportunity t...
The goal of Primary Care is the optimization of individual and population health through timely, evidence-based care and prevention at the lowest cost. Direct Primary Care (DPC) is a compelling ambulatory practice model that aims to remove patient barriers to access and provide timely and personalized preventive and first-line care for a fixed peri...
This study provides a qualitative analysis of the effects of the COVID-19 pandemic on the nutritional and physical activity self-management of adults with Type 2 diabetes (T2D). We conducted semi-structured interviews with 21 adults with T2D living in the United States, and recorded their experiences maintaining and/or modifying their self-manageme...
While the availability of large-scale online recipe collections presents opportunities for health consumers to access a wide variety of recipes, it can be challenging for them to discover relevant recipes. Whereas most recommender systems are designed to offer selections consistent with users’ past behavior, it remains an open problem to offer sele...
Introduction
Across the U.S., the prevalence of opioid use disorder (OUD) and the rates of opioid overdoses have risen precipitously in recent years. Several effective medications for OUD (MOUD) exist and have been shown to be life-saving. A large volume of research has identified a confluence of factors that predict attrition and continued substan...
We propose a knowledge model for capturing dietary preferences and personal context to provide personalized dietary recommendations. We develop a knowledge model called the Personal Health Ontology, which is grounded in semantic technologies, and represents a patient's combined medical information, social determinants of health, and observations of...
Although it has become easier for individuals to track their personal health data (e.g., heart rate, step count, and nutrient intake data), there is still a wide chasm between the collection of data and the generation of meaningful summaries to help users better understand what their data means to them. With an increased comprehension of their data...
Academic advances of AI models in high-precision domains, like healthcare, need to be made explainable in order to enhance real-world adoption. Our past studies and ongoing interactions indicate that medical experts can use AI systems with greater trust if there are ways to connect the model inferences about patients to explanations that are tied b...
Using real-world data from the Academy of Nutrition and Dietetics Health Informatics Infrastructure, we use state-of-the-art clustering techniques to identify 2 phenotypes characterizing the episodes of nutrition care observed in the National Quality Improvement (NQI) registry data set. The 2 phenotypes identified from recorded Nutrition Care Proce...
People can affect change in their eating patterns by substituting ingredients in recipes. Such substitutions may be motivated by specific goals, like modifying the intake of a specific nutrient or avoiding a particular category of ingredients. Determining how to modify a recipe can be difficult because people need to 1) identify which ingredients c...
Food recommendation has become an important means to help guide users to adopt healthy dietary habits. Previous works on food recommendation either i) fail to consider users' explicit requirements, ii) ignore crucial health factors (e.g., allergies and nutrition needs), or iii) do not utilize the rich food knowledge for recommending healthy recipes...
Recent advances in wearable sensor technologies have led to a variety of approaches for detecting physiological stress. Even with over a decade of research in the domain, there still exist many significant challenges, including a near-total lack of reproducibility across studies. Researchers often use some physiological sensors (custom-made or off-...
Health risk behaviors are leading contributors to morbidity, premature mortality associated with chronic diseases, and escalating health costs. However, traditional interventions to change health behaviors often have modest effects, and limited applicability and scale. To better support health improvement goals across the care continuum, new approa...
The health outcomes of high-need patients can be substantially influenced by the degree of patient engagement in their own care. The role of care managers (CMs) includes enrolling patients and keeping them sufficiently engaged in care programs, so that patients complete assigned goals leading to improvement in their health outcomes. Here, we presen...
Whereas it has become easier for individuals to track their personal health data (e.g., heart rate, step count, food log), there is still a wide chasm between the collection of data and the generation of meaningful explanations to help users better understand what their data means to them. With an increased comprehension of their data, users will b...
Objective
To improve efficient goal attainment of patients by analyzing the unstructured text in care manager (CM) notes (CMNs). Our task is to determine whether the goal assigned by the CM can be achieved in a timely manner.
Materials and Methods
Our data consists of CM structured and unstructured records from a private firm in Orlando, FL. The C...
The application of digital technologies to better assess, understand, and treat substance use disorders (SUDs) is a particularly promising and vibrant area of scientific research. The National Drug Abuse Treatment Clinical Trials Network (CTN), launched in 1999 by the U.S. National Institute on Drug Abuse, has supported a growing line of research t...
The factors that define and influence the success of industry–academic research in artificial intelligence have evolved significantly in the last decade. In this article, we consider what success means from both sides of a collaboration and offer our perspectives on how to approach the opportunities and challenges that come with achieving success....
This article contains the observations of Yolanda Gil, director of knowledge technologies and research professor at the Information Sciences Institute of the University of Southern California, USA, and president of Association for Advancement of Artificial Intelligence who was recently interviewed about the factors that could influence successful A...
This article contains the observations of Arvind Gupta, who has over 22 years of experience in leadership, policy, and entrepreneurial roles, in both the Silicon Valley and India. Gupta was recently interviewed about the factors that could influence successful artificial intelligence research. At the time of the interview, Gupta was the chief execu...
This editorial introduces the special topic articles on reflections on successful research in artificial intelligence. Consisting of a combination of interviews and full-length articles, the special topic articles examine the meaning of success and metrics of success from a variety of perspectives. Our editorial team is especially excited about thi...
We demonstrate the usage of our FoodKG [3], a food knowl- edge graph designed to assist in food recommendation. This resource, which brings together recipes, nutrition, food taxonomies, and links into existing ontologies, is used to power a cognitive agent that performs knowledge-base question answering, primarily to help improve peoples' diets by...
The proliferation of recipes and other food information on the Web presents an opportunity for discovering and organizing diet-related knowledge into a knowledge graph. Currently, there are several ontologies related to food, but they are specialized in specific domains, e.g., from an agricultural, production, or specific health condition point-of-...
Listening to music has been studied as a method for combating the rapidly increasing stress levels of adolescents. Previous studies yielded inconsistent results and neglected specific factors including the time relative to the stressor and the duration of time in which participants listened to music. We conducted a survey and lab experiment to inve...
Online health communities (OHCs) have become popular online environments for patients seeking and sharing treatment experiences. These platforms enable us to move beyond traditional sources of clinical information for learning about a patient’s long-term adherence to treatment. In spite of this opportunity, large-scale self-composed online free tex...
The health outcomes of high-need patients can be substantially influenced by the degree of patient engagement in their own care. The role of care managers includes that of enrolling patients into care programs and keeping them sufficiently engaged in the program, so that patients can attain various goals. The attainment of these goals is expected t...
In recent years, there has been growing interest in the use of fitness trackers and smartphone applications for promoting physical activity. Most of these applications use accelerometers to measure the level of activity that users engage in and provide descriptive, interactive reports of a user's step counts. While these reports are data-driven and...
The advances in mobile and wearable sensing have led to a myriad of approaches for stress detection in both laboratory and free-living settings. Most of these methods, however, rely on the usage of some combination of physiological signals measured by the sensors to detect stress. While these solutions work great in a lab or a controlled environmen...
Psychological stress is a major contributor to the adoption of unhealthy behaviors, which in turn accounts for 41% of global cardiovascular disease burden. While the proliferation of mobile health apps has offered promise to stress management, these apps do not provide micro-level feedback with regard to how to adjust one's behaviors to achieve a d...
An increasing number of people use mobile devices to monitor their behavior, such as exercise, and record their health status, such as psychological stress. However, these devices rarely provide ongoing support to help users understand how their behavior contributes to changes in their health status. To address this challenge, we aim to develop an...
Person-generated health data (PGHD) generated by wearable devices and smartphone applications are growing rapidly. There is increasing effort to employ advanced analytical methods to generate insights from these data in order to help people change their lifestyle and improve their health. PGHD—such as step counts, exercise logs, nutritional diaries...
Psychological stress is a major contributor to the adoption of unhealthy behaviors, which in turn accounts for 41% of global cardiovascular disease burden. While the proliferation of mobile health apps has offered promise to stress management, these apps do not provide micro-level feedback with regard to how to adjust one’s behaviors to achieve a d...
Social media platforms have become popular online environments for patients seeking and sharing treatment experiences. These platforms enable us to move beyond traditional sources of clinical information for learning about a patient's long-term adherence to treatment. While adherence has been studied using data derived from medical records and stru...
A DeepQA engine is enhanced to provide a digital medical investigation tool which assists a medical professional in researching potential causes of a set of patient conditions, including clues, facts and factoids about the patient. The DeepQA engine provides one or more answers to a natural language question with confidence levels for each answer....
Results from laboratory tests of commercially available photosensors and ballasts are applied in a detailed computer model of a private office considering a variety of window and daylighting conditions. The laboratory measurements include directional sensitivity, impact of calibration setting adjustments, and the relative sensitivity of the photose...
At WinterSim 2011, we originally proposed an agent-based framework for healthcare simulations, enabling flexible integration of multiple simulation models, including models of disease progression, effects of provider interventions, and provider behavior models that are responsive to contractual incentives. In this paper, we report results using our...
Healthcare transformation through the use of information technologies is partly dependent on effectively applying the most up-to-date knowledge to the complete representation of the patient's past medical history at the point of care. In order for health ...
We present a general simulation framework designed for modeling incentives in a health care delivery system. This first version of the framework focuses on representing provider incentives. Key framework components are described in detail, and we provide an overview of how data-driven analytic methods can be integrated with this framework to enable...
Rising costs, decreasing quality of care, diminishing productivity, and increasing complexity have all contributed to the present state of the healthcare industry. The interactions between payers (e.g., insurance companies and health plans) and providers (e.g., hospitals and laboratories) are growing and are becoming more complicated. The constant...
The use of reverse auctions for procurement activities has grown tremendously over the last several years. The majority of these auctions use a single dimension (price) format while providing constraints on non-price attributes such as quality and lead time. In this research, we present an auction mechanism for a buyer whose utility function is kno...
We describe a discrete event simulator that has been deployed in a 300 mm wafer fabrication plant to aid short-term, operational decision-making. Our simulator has been designed and calibrated to produce reliable predictions over simulation horizons as short as a few days to several weeks. It has been automated to run daily, without the need for ma...
We address the problem of rationing common components among multiple products in a configure-to-order system with order configuration uncertainty. The objective of this problem is to maximize expected revenue by implementing a threshold rationing policy. Under this policy, a product is available to promise if fulfilling the order for the product wi...
This paper addresses the problem of aligning demand and supply in configure-to-order systems. Using stochastic programming methods, this study demonstrates the value of accounting for the uncertainty associated with how orders are configured. We also demonstrate the value of component supply flexibility in the presence of order configuration uncert...
During the last 50 years, population growth, along with increasingly affluent societies, has resulted in a greater demand for our limited physical infrastructures and natural resources than ever before. In addition, the risks of climate change have heightened the need for more sophisticated ways of controlling carbon emissions. Today, numerous stre...
We describe a discrete event simulator developed for daily prediction of WIP position in an operational 300 mm wafer fabrication factory to support tactical decision-making. The simulator is distinctive in that its intended prediction horizon is relatively short, on the order of a few days, while its modeling scope is relatively large. The simulati...
At the IBM T. J. Watson Research Center, the Watson Women's Network (WWN) devised an innovative format for a networking event to facilitate professional networking between IBM's technical and business communities. The WWN organized two networking events based on the devised event format. We used social network analysis and other methods to show tha...
We describe a discrete event simulator developed for daily prediction of WIP position in an operational 300 mm wafer fabrication factory to support tactical decision-making. The simulator is distinctive in that its intended prediction horizon is relatively short, on the order of a few days, while its modeling scope is relatively large. The simulati...
The majority of reverse auctions for procurement use a single-attribute (price) format while providing constraints on nonprice attributes such as quality and lead time. Alternatively, a buyer could choose to conduct a multiattribute auction where bidders can specify both a price and levels of nonprice attributes. While such an auction may provide h...
The use of reverse auctions for procurement activities has grown tremendously over the last several years. The majority of these auctions use a single dimension (price) format while providing constraints on non-price attributes such as quality and lead time. In this research, we present an auction mechanism for a buyer whose utility function is kno...
An important healthcare problem in the United States of America is that of emergency department overcrowding. A plausible explanation for such overcrowding is that the lack of access to primary care, which may be influenced by one's insurance status, leads to greater use of emergency departments. Additionally, it has been suggested that the inappro...
