Analysis of article using Artificial Intelligence tools
Id | 2449 | |
Author | Zarkogianni K.; Chatzidaki E.; Polychronaki N.; Kalafatis E.; Nicolaides N.C.; Voutetakis A.; Chioti V.; Kitani R.-A.; Mitsis K.; Perakis Κ.; Athanasiou M.; Antonopoulou D.; Pervanidou P.; Kanaka-Gantenbein C.; Nikita K. | |
Title | The ENDORSE Feasibility Study: Exploring the Use of M-Health, Artificial Intelligence and Serious Games for the Management of Childhood Obesity | |
Reference | Zarkogianni K.; Chatzidaki E.; Polychronaki N.; Kalafatis E.; Nicolaides N.C.; Voutetakis A.; Chioti V.; Kitani R.-A.; Mitsis K.; Perakis Κ.; Athanasiou M.; Antonopoulou D.; Pervanidou P.; Kanaka-Gantenbein C.; Nikita K. The ENDORSE Feasibility Study: Exploring the Use of M-Health, Artificial Intelligence and Serious Games for the Management of Childhood Obesity,Nutrients 15 6 |
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Keywords | Artificial Intelligence; Body Mass Index; Child; Ecosystem; Feasibility Studies; Female; Humans; Male; Pediatric Obesity; Telemedicine; artificial intelligence; body mass; child; childhood obesity; ecosystem; feasibility study; female; human; male; telemedicine |
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Link to article | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151108061&doi=10.3390%2fnu15061451&partnerID=40&md5=1d95f2c06266f3c1dcb5ce14e82bcbfc |
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Abstract | Childhood obesity constitutes a major risk factor for future adverse health conditions. Multicomponent parent-child interventions are considered effective in controlling weight. Τhe ENDORSE platform utilizes m-health technologies, Artificial Intelligence (AI), and serious games (SG) toward the creation of an innovative software ecosystem connecting healthcare professionals, children, and their parents in order to deliver coordinated services to combat childhood obesity. It consists of activity trackers, a mobile SG for children, and mobile apps for parents and healthcare professionals. The heterogeneous dataset gathered through the interaction of the end-users with the platform composes the unique user profile. Part of it feeds an AI-based model that enables personalized messages. A feasibility pilot trial was conducted involving 50 overweight and obese children (mean age 10.5 years, 52% girls, 58% pubertal, median baseline BMI z-score 2.85) in a 3-month intervention. Adherence was measured by means of frequency of usage based on the data records. Overall, a clinically and statistically significant BMI z-score reduction was achieved (mean BMI z-score reduction -0.21 ± 0.26, p-value < 0.001). A statistically significant correlation was revealed between the level of activity tracker usage and the improvement of BMI z-score (-0.355, p = 0.017), highlighting the potential of the ENDORSE platform. |
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Metodology | Technique |