Data-as-a-Service Platform for Delivering Healthy Lifestyle and Preventive Medicine: Concept and Structure of the DAPHNE Project
Notice bibliographique
Résumé
BACKGROUND: Overweight and obesity is related to many health problems and diseases. The current obesity epidemic, which is a major health problem, is closely related to a lack of physical activity, high levels of sedentary behavior, and increased energy intake; with evidence to show increasing incidence of these issues in the younger population. Tackling obesity and its comorbid conditions requires a holistic approach encompassing attention on physical activity, healthy diet, and behavioral activation in order to enable and maintain meaningful and long-term weight loss and weight maintenance. OBJECTIVE: The objective of the Data-as-a-Service Platform for Healthy Lifestyle and Preventive Medicine (DAPHNE) project is to develop a breakthrough information communications technology (ICT) platform for tracking health, weight, physical activity, diet, lifestyle, and psychological components within health care systems, whereby the platform and clinical support is linked. METHODS: The DAPHNE platform aims to deliver personalized guidance services for lifestyle management to the citizen/patient by means of (1) advanced sensors and mobile phone apps to acquire and store continuous/real-time data on lifestyle aspects, behavior, and surrounding environment; (2) individual models to monitor their health and fitness status; (3) intelligent data processing for the recognition of behavioral trends; and (4) specific services for personalized guidance on healthy lifestyle and disease prevention. It is well known that weight loss and maintenance of weight loss are particularly difficult. This tool will address some of the issues found with conventional treatment/advice in that it will collect data in real time, thereby reducing reliability issues known with recalling events once they have passed and will also allow adjustment of behavior through timely support and recommendations sent through the platform without the necessity of formal one-to-one visits between patient and clinician. Patient motivation/compliance is a particular issue with conventional weight loss regimes; DAPHNE aims to increase the individuals' awareness of their own behavior and fosters their accountability. RESULTS: The project has been funded and the research work has started. Results for the validation of the different components is due imminently. CONCLUSIONS: In contrast with previous existing solutions, the DAPHNE project tackles the obesity problem from a clinical point of view, designing the different interfaces for its use by patients (adults and children), physicians, and caregivers. A specific design for children and adolescent patients treated for obesity has been followed, guided by pediatric physicians at hospitals in Europe. The final clinical validation of the DAPHNE platform will be carried out in different European hospitals, testing the platform in both adolescents and adults.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,008 | 0,013 |
| Science ouverte | 0,004 | 0,020 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,005 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».