Published on in Vol 10, No 6 (2022): June
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/33847, first published
.
Journals
- Chatterjee A, Pahari N, Prinz A, Riegler M. Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation. Scientific Reports 2022;12(1) View
- Chatterjee A, Prinz A, Gerdes M, Martinez S, Pahari N, Meena Y. ProHealth eCoach: user-centered design and development of an eCoach app to promote healthy lifestyle with personalized activity recommendations. BMC Health Services Research 2022;22(1) View
- Chatterjee A, Prinz A, Riegler M, Das J. A systematic review and knowledge mapping on ICT-based remote and automatic COVID-19 patient monitoring and care. BMC Health Services Research 2023;23(1) View
- Premanandan S, Ahmad A, Cajander Å, Ågerfalk P, Dolezel M, van Gemert-Pijnen L. Designing a Mobile e-Coaching App for Immigrant Informal Caregivers: Qualitative Study Using the Persuasive System Design Model. JMIR mHealth and uHealth 2023;11:e50038 View
- Jafar N, Huriyati E, Haryani , Setyawati A. Enhancing knowledge of Diabetes self-management and quality of life in people with Diabetes Mellitus by using Guru Diabetes Apps-based health coaching. Journal of Public Health Research 2023;12(3) View
- Chatterjee A, Prinz A, Riegler M, Meena Y. An automatic and personalized recommendation modelling in activity eCoaching with deep learning and ontology. Scientific Reports 2023;13(1) View
- Chatterjee A, Pahari N, Prinz A, Riegler M. AI and semantic ontology for personalized activity eCoaching in healthy lifestyle recommendations: a meta-heuristic approach. BMC Medical Informatics and Decision Making 2023;23(1) View
- Chatterjee A, Gerdes M, Prinz A, Riegler M, Martinez S. Semantic representation and comparative analysis of physical activity sensor observations using MOX2-5 sensor in real and synthetic datasets: a proof-of-concept-study. Scientific Reports 2024;14(1) View
- Yu C, Zong H, Chen Y, Zhou Y, Liu X, Lin Y, Li J, Zheng X, Min H, Shen B. PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data. Briefings in Bioinformatics 2024;25(3) View
- Chatterjee A, Riegler M, Johnson M, Das J, Pahari N, Ramachandra R, Ghosh B, Saha A, Bajpai R. Exploring online public survey lifestyle datasets with statistical analysis, machine learning and semantic ontology. Scientific Reports 2024;14(1) View