Ontology-based decision support systems for diabetes nutrition therapy: A systematic literature review

Diabetes is a non-communicable disease that has reached epidemic proportions, affecting 537 million people globally. Artificial Intelligence can support patients or clinicians in diabetes nutrition therapy - the first medical therapy in most cases of Type 1 and Type 2 diabetes. In particular, ontology-based recommender and decision support systems can deliver a computable representation of experts' knowledge, thus delivering patient-tailored nutritional recommendations or supporting clinical personnel in identifying the most suitable diet. This work proposes a systematic literature review of the domain ontologies describing diabetes in such systems, identifying their underlying conceptualizations, the users targeted by the systems, the type(s) of diabetes tackled, and the nutritional recommendations provided. This review also delves into the structure of the domain ontologies, highlighting several aspects that may hinder (or foster) their adoption in recommender and decision support systems for diabetes nutrition therapy. The results of this review process allow to underline how recommendations are formulated and the role of clinical experts in developing domain ontologies, outlining the research trends characterizing this research area. The results also allow for identifying research directions that can foster a preeminent role for clinical experts and clinical guidelines in a cooperative effort to make ontologies more interoperable - thus enabling them to play a significant role in the decision-making processes about diabetes nutrition therapy.

A Knowledge-based Decision Support System for recommending safe recipes to individuals with dysphagia

BACKGROUND

Dysphagia is a disorder that can be associated to several pathological conditions, including neuromuscular diseases, with significant impact on quality of life. Dysphagia often leads to malnutrition, as a consequence of the dietary changes made by patients or their caregivers, who may deliberately decide to reduce or avoid specific food consistencies (because they are not perceived as safe), and the lack of knowledge in how to process foods are critics. Such dietary changes often result in unbalanced nutrients intake, which can have significant consequences for frail patients. This paper presents the development of a prototypical novel ontology-based Decision Support System (DSS) to support neuromuscular patients with dysphagia (following a per-oral nutrition) and their caregivers in preparing nutritionally balanced and safe meals.

METHOD

After reviewing scientific literature, we developed in collaboration with Ear-Nose-Throat (ENT) specialists, neurologists, and dieticians the DSS formalizes expert knowledge to suggest recipes that are considered safe according to patient's consistency limitations and dysphagia severity and also nutritionally well-balanced.

RESULTS

The prototype can be accessed via digital applications both by physicians to generate and verify the recommendations, and by the patients and their caregivers to follow the step-by-step procedures to autonomously prepare and process one or more recipe. The system is evaluated with 9 clinicians to assess the quality of the DSS's suggested recipes and its acceptance in clinical practice.

CONCLUSIONS

Preliminary results suggest a global positive outcome for the recipes inferred by the DSS and a good usability of the system.

Proposal for an ICF-based methodology to foster the return to work of persons with disability

BACKGROUND

Employment is an essential component of life as it provides income, sense of engagement and opportunities for personal development. Unemployment due to disability following an accident may have dramatic social and psychological consequences on individuals; it is thus fundamental to foster return to work of these persons.

OBJECTIVE

The present work was aimed to develop a methodology determining suitable jobs for people living with disability after a job-related accident.

METHODS

The Occupational Information Network (O*NET) taxonomy was combined with the International Classification of Functioning, Disability and Health (ICF) to match individual resources with specific job requirements. ICF Linking Rules were employed by two independent groups of researchers to associate ICF codes to O*NET skill and ability descriptors.

RESULTS

O*NET descriptors were linked to 92 unique ICF codes. A "Criticality score" combining ICF and O*NET features to assess suitability of selected jobs for persons with disabilities was also proposed.

CONCLUSIONS

The proposed methodology represents a novel instrument to support return to work; the capability to assess specific work-related facets through the lens of both the ICF model and O*NET taxonomy would conceivably provide vocational rehabilitation specialists and occupational therapists with a useful tool fostering job placement of workers with disability.

Cabin as a Home: A Novel Comfort Optimization Framework for IoT Equipped Smart Environments and Applications on Cruise Ships

The international tourism competition poses new challenges to the cruise sector, such as the achievement of the tourists' satisfaction and the increase in on board comfort. Moreover, the growing sophistication of tourists' needs leads to a more user-centric touristic offer. Consequently, a personalized cabin environment, which fits the users' activities and their characteristics, could be a plus value during the cruise vacation. These topics, however, are strictly connected with the diffusion of digital technologies and dynamics, which represent the tools to achieve the goal of a customized on-cruise experience. This paper presents E-Cabin, a novel Internet of Things (IoT) framework architecture that has at its core a reasoning system tuned on data gathered from the environment and from each specific passenger and the activities he/she performs. The framework leverages on knowledge representation with ontologies and consists of a publisher⁻subscriber communication framework that allows all of the IoT applications to use the reasoner and the provided ontologies. The paper demonstrates the proposed system in a demo cruise cabin where, by using the E-Cabin application, it is possible to set various atmospheres based on the users and activities occurring in the cabin.

Analysis for the design of a novel integrated framework for the return to work of wheelchair users

BACKGROUND

Return to work represents an important milestone for workers who were injured during a workplace accident, especially if the injury results in needing a wheelchair for locomotion.

OBJECTIVE

The aim of the study was to design a framework for training novice wheelchair users in regaining autonomy in activities of daily living and in the workplace and for providing medical personnel with objective data on users' health and work-related capabilities.

METHODS

The framework design was accomplished following the "Usability Engineering Life Cycle" model. According to it, three subsequent steps defined as "Know your User", "Competitive Analysis" and "Participatory Design" have been carried out to devise the described framework.

RESULTS

The needs of the end-users of the framework were identified during the first phase; the Competitive Analysis phase addressed standard care solutions, Virtual Reality-based wheelchair simulators, the current methodologies for the assessment of the health condition of people with disability and the use of semantic technologies in human resources. The Participatory Design phase led to the definition of an integrated user-centred framework supporting the return to work of wheelchair users.

CONCLUSION

The results of this work consists in the design of an innovative training process based on virtual reality scenarios and supported by semantic web technologies. In the near future, the design process will proceed in collaboration with the Italian National Institute for Insurance against Accidents at Work (INAIL). The whole framework will be then implemented to support the current vocational rehabilitation process within INAIL premises.