OBINTER: A Holistic Approach to Catalyse the Self-Management of Chronic Obesity

Álvarez, Roberto; Torres, Jordi; Artola, Garazi; Epelde, Gorka; Arranz, Sara; Marrugat, Gerard

doi:10.3390/s20185060

Cited by 6 publications

(3 citation statements)

References 45 publications

(39 reference statements)

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“…Dietician is involved when it is difficult to control diet and a nutritional balance. Useful solutions for children could be enabled through mobile apps and gaming [27] (organizational aspects are addressed mainly on the management of the mobile app data)…”

Section: Dieticianmentioning

confidence: 99%

Process Mining Organization (PMO) Based on Machine Learning Decision Making for Prevention of Chronic Diseases

Rosa,

Massaro

2024

Eng

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This paper discusses a methodology to improve the prevention processes of chronic diseases such as diabetes and strokes. The research motivation is to find a new methodological approach to design advanced Diagnostic and Therapeutic Care Pathways (PDTAs) based on the prediction of chronic disease using telemedicine technologies and machine learning (ML) data processing techniques. The aim is to decrease health risk and avoid hospitalizations through prevention. The proposed method defines a Process Mining Organization (PMO) model, managing risks using a PDTA structured to prevent chronic risk. Specifically, the data analysis is focused on stroke risk. First, we applied and compared the Random Forest (RF) and Gradient Boosted Trees (GBT) supervised algorithms to predict stroke risk, and then, the Fuzzy c-Means unsupervised algorithm to cluster information on the predicted results. The application of the proposed approach is able to increase the efficiency of healthcare human resources and drastically decrease care costs.

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Section: Dieticianmentioning

confidence: 99%

Process Mining Organization (PMO) Based on Machine Learning Decision Making for Prevention of Chronic Diseases

Rosa,

Massaro

2024

Eng

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“…Meanwhile, technological advancements in wearable sensors help to monitor the treatment efficacy and help in the early detection of the risk of obesity and its comorbidities by measuring heart rate, respiratory rate, temperature, and blood pressure [ 162 , 163 ]. Wearable devices are also very useful tools for self-management and physical activity tracking [ 164 ].…”

Section: Limitations and Future Perspectivesmentioning

confidence: 99%

The Related Metabolic Diseases and Treatments of Obesity

2022

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Obesity is a chronic disease characterized by the abnormal or excessive accumulation of body fat, affecting more than 1 billion people worldwide. Obesity is commonly associated with other metabolic disorders, such as type 2 diabetes, non-alcoholic fatty liver disease, cardiovascular diseases, chronic kidney disease, and cancers. Factors such as a sedentary lifestyle, overnutrition, socioeconomic status, and other environmental and genetic conditions can cause obesity. Many molecules and signaling pathways are involved in the pathogenesis of obesity, such as nuclear factor (NF)-κB, Toll-like receptors (TLRs), adhesion molecules, G protein-coupled receptors (GPCRs), programmed cell death 1 (PD-1)/programmed death-ligand 1 (PD-L1), and sirtuin 1 (SIRT1). Commonly used strategies of obesity management and treatment include exercise and dietary change or restriction for the early stage of obesity, bariatric surgery for server obesity, and Food and Drug Administration (FDA)-approved medicines such as semaglutide and liraglutide that can be used as monotherapy or as a synergistic treatment. In addition, psychological management, especially for patients with obesity and distress, is a good option. Gut microbiota plays an important role in obesity and its comorbidities, and gut microbial reprogramming by fecal microbiota transplantation (FMT), probiotics, prebiotics, or synbiotics shows promising potential in obesity and metabolic syndrome. Many clinical trials are ongoing to evaluate the therapeutic effects of different treatments. Currently, prevention and early treatment of obesity are the best options to prevent its progression to many comorbidities.

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“…We have conducted a formal usability test with a set of test subjects matching the target tool user profiles as has been done in the literature for similar platforms [ 25 , 26 ]. These individuals had no prior experience with the tool to avoid bias in their evaluation of COLAEVA.…”

Section: Usability Testmentioning

confidence: 99%

COLAEVA: Visual Analytics and Data Mining Web-Based Tool for Virtual Coaching of Older Adult Populations

Kerexeta

Beristáin

Álvarez

et al. 2021

Sensors

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The global population is aging in an unprecedented manner and the challenges for improving the lives of older adults are currently both a strong priority in the political and healthcare arena. In this sense, preventive measures and telemedicine have the potential to play an important role in improving the number of healthy years older adults may experience and virtual coaching is a promising research area to support this process. This paper presents COLAEVA, an interactive web application for older adult population clustering and evolution analysis. Its objective is to support caregivers in the design, validation and refinement of coaching plans adapted to specific population groups. COLAEVA enables coaching caregivers to interactively group similar older adults based on preliminary assessment data, using AI features, and to evaluate the influence of coaching plans once the final assessment is carried out for a baseline comparison. To evaluate COLAEVA, a usability test was carried out with 9 test participants obtaining an average SUS score of 71.1. Moreover, COLAEVA is available online to use and explore.

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OBINTER: A Holistic Approach to Catalyse the Self-Management of Chronic Obesity

Cited by 6 publications

References 45 publications

Process Mining Organization (PMO) Based on Machine Learning Decision Making for Prevention of Chronic Diseases

Process Mining Organization (PMO) Based on Machine Learning Decision Making for Prevention of Chronic Diseases

The Related Metabolic Diseases and Treatments of Obesity

COLAEVA: Visual Analytics and Data Mining Web-Based Tool for Virtual Coaching of Older Adult Populations

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