Combining data-driven and domain knowledge components in an intelligent assistant to build personalized menus

In this paper, some new components that have been integrated in the Diet4You system for the generation of nutritional plans are introduced. Negative user preferences have been modelled and introduced in the system. Furthermore, the cultural eating styles originated from the location where the user lives have been taken into account dividing the original menu plan in sub-plans. Each sub-plan is in charge to optimize one of the meals of one day in the personal menu of the user. The main latent reasoning mechanism used is case-based reasoning, which reuses previous menu configurations according to the nutritional plan and the corresponding hard constraints and the user preferences to meet a personalized recommendation menu for a given user. It uses the cognitive analogical reasoning technique in addition to ontologies, nutritional databases and expert knowledge. The preliminary results with some examples of application to test the new contextual components have been very satisfactory according to the evaluation of the experts.This work has been partially supported by the project Diet4You (TIN2014-60557-R), the Spanish Thematic Network MAPAS [TIN2017-90567-REDT (MINECO/FEDER EU)], and the Consolidated Research Group Grant from AGAUR (Generalitat de Catalunya) IDEAI-UPC (AGAUR SGR2017-574).Peer ReviewedPostprint (author's final draft

Strategies for online personalised nutrition advice employed in the development of the eNutri web app

The internet has considerable potential to improve health-related food choice at low-cost. Online solutions in this field can be deployed quickly and at very low cost, especially if they are not dependent on bespoke devices or offline processes such as the provision and analysis of biological samples. One key challenge is the automated delivery of personalised dietary advice in a replicable, scalable and inexpensive way, using valid nutrition assessment methods and effective recommendations. We have developed a web-based personalised nutrition system (eNutri) which assesses dietary intake using a validated graphical FFQ and provides personalised food-based dietary advice automatically. Its effectiveness was evaluated during an online randomised controlled trial dietary intervention (EatWellUK study) in which personalised dietary advice was compared with general population recommendations (control) delivered online. The present paper presents a review of literature relevant to this work, and describes the strategies used during the development of the eNutri app. Its design and source code have been made publicly available under a permissive open source license, so that other researchers and organisations can benefit from this work. In a context where personalised diet advice has great potential for health promotion and disease prevention at-scale and yet is not currently being offered in the most popular mobile apps, the strategies and approaches described in the present paper can help to inform and advance the design and development of technologies for personalised nutrition

Artificial intelligence within the interplay between natural and artificial computation:Advances in data science, trends and applications

Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in artificial intelligence and machine learning to the most prospective applications in robotics, neuroscience, brain computer interfaces, medicine and society, in general.BMS - Pfizer(U01 AG024904). Spanish Ministry of Science, projects: TIN2017-85827-P, RTI2018-098913-B-I00, PSI2015-65848-R, PGC2018-098813-B-C31, PGC2018-098813-B-C32, RTI2018-101114-B-I, TIN2017-90135-R, RTI2018-098743-B-I00 and RTI2018-094645-B-I00; the FPU program (FPU15/06512, FPU17/04154) and Juan de la Cierva (FJCI-2017–33022). Autonomous Government of Andalusia (Spain) projects: UMA18-FEDERJA-084. Consellería de Cultura, Educación e Ordenación Universitaria of Galicia: ED431C2017/12, accreditation 2016–2019, ED431G/08, ED431C2018/29, Comunidad de Madrid, Y2018/EMT-5062 and grant ED431F2018/02. PPMI – a public – private partnership – is funded by The Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbott, Biogen Idec, F. Hoffman-La Roche Ltd., GE Healthcare, Genentech and Pfizer Inc

Generating complete menus from nutritional prescriptions by using advanced CBR and Real Food Databases

Prevention and nutrition are key issues to guarantee a healthy lifestyle and are in the kernel of the new paradigm of patient-centered medicine. A healthy diet protects against risk factors of a large number of chronic diseases and contribute to delay the disease appearance in the general population. More and more, making right diets is becoming essential from the health point of view. However, nutritionists design diets on the specific needs of each patient, using their accumulated experience and there are no well-formalized support mechanisms for such activity. The project Diet4You proposes the creation of an intelligent decision support system oriented to the adaptive and dynamic preparation of personalized diets for the specific individuals of general population, having or not, one or more diseases, by taking into account all the information available on the person. The diets will be built by considering the characteristics of the person, their health conditions, their habits and eventual drugs intake and their genetic information, which until now were not taken into account. The Diet4You tool is a hybrid system interacting several components in a complex way. One of those components is a subsystem able to compose complete menus, for a certain period of time, based on the nutritional prescriptions given by the nutritionists, in terms of balance of different families of nutrients. This component is based on a a Case-Based Reasoning (CBR) engine that adaptively creates menus with breakfast, lunch and dinner on the bases of real food databases containing dishes with their nutritional composition. In this work, this component of the whole system is presented, described and tested.Peer ReviewedPostprint (author's final draft

Generating complete menus from nutritional prescriptions by using advanced CBR and Real Food Databases

Prevention and nutrition are key issues to guarantee a healthy lifestyle and are in the kernel of the new paradigm of patient-centered medicine. A healthy diet protects against risk factors of a large number of chronic diseases and contribute to delay the disease appearance in the general population. More and more, making right diets is becoming essential from the health point of view. However, nutritionists design diets on the specific needs of each patient, using their accumulated experience and there are no well-formalized support mechanisms for such activity. The project Diet4You proposes the creation of an intelligent decision support system oriented to the adaptive and dynamic preparation of personalized diets for the specific individuals of general population, having or not, one or more diseases, by taking into account all the information available on the person. The diets will be built by considering the characteristics of the person, their health conditions, their habits and eventual drugs intake and their genetic information, which until now were not taken into account. The Diet4You tool is a hybrid system interacting several components in a complex way. One of those components is a subsystem able to compose complete menus, for a certain period of time, based on the nutritional prescriptions given by the nutritionists, in terms of balance of different families of nutrients. This component is based on a a Case-Based Reasoning (CBR) engine that adaptively creates menus with breakfast, lunch and dinner on the bases of real food databases containing dishes with their nutritional composition. In this work, this component of the whole system is presented, described and tested.Peer Reviewe

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

2012 - 2013 University Catalog

Volume 102, Number 1, July 2012 Published once a year, July 2012https://scholarsrepository.llu.edu/univcatalog/1004/thumbnail.jp

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios