This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1210) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (591) Wearable Devices and Sensors (903) Heart Failure Self-Management (155) Mobile Apps for Cardiology (144) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1428) Mobile Health (mhealth) (2982) Clinical Information and Decision Making (1434) User-centred Design Case Studies (602) Human Factors and Usability Case Studies (809)

Published on in Vol 9, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24501, first published .
A Personal Health System for Self-Management of Congestive Heart Failure (HeartMan): Development, Technical Evaluation, and Proof-of-Concept Randomized Controlled Trial

A Personal Health System for Self-Management of Congestive Heart Failure (HeartMan): Development, Technical Evaluation, and Proof-of-Concept Randomized Controlled Trial

A Personal Health System for Self-Management of Congestive Heart Failure (HeartMan): Development, Technical Evaluation, and Proof-of-Concept Randomized Controlled Trial

Authors of this article:

Mitja Luštrek1 Author Orcid Image ;   Marko Bohanec2 Author Orcid Image ;   Carlos Cavero Barca3 Author Orcid Image ;   Maria Costanza Ciancarelli4 Author Orcid Image ;   Els Clays5 Author Orcid Image ;   Amos Adeyemo Dawodu4 Author Orcid Image ;   Jan Derboven6 Author Orcid Image ;   Delphine De Smedt5 Author Orcid Image ;   Erik Dovgan1 Author Orcid Image ;   Jure Lampe7 Author Orcid Image ;   Flavia Marino8 Author Orcid Image ;   Miha Mlakar1 Author Orcid Image ;   Giovanni Pioggia8 Author Orcid Image ;   Paolo Emilio Puddu4 Author Orcid Image ;   Juan Mario Rodríguez3 Author Orcid Image ;   Michele Schiariti4 Author Orcid Image ;   Gašper Slapničar1 Author Orcid Image ;   Karin Slegers9 Author Orcid Image ;   Gennaro Tartarisco8 Author Orcid Image ;   Jakob Valič1 Author Orcid Image ;   Aljoša Vodopija1 Author Orcid Image
Article Authors Cited by (21) Tweetations (3) Metrics

Journals

  1. Cestari V, Florêncio R, Garces T, Souza L, Negreiros F, Pessoa V, Moreira T. CODESIGN OF A CARE-EDUCATIONAL APP FOR PEOPLE WITH HEART FAILURE: DESIGN, PROTOTYPING AND CO-IMPLEMENTATION. Texto & Contexto - Enfermagem 2022;31 View
  2. Farzandipour M, Nabovati E, Farrokhian A, Akbari H, Rezaei hasanvand F, Sharif R. Designing and usability assessing an electronic personal health record for patients with chronic heart failure in a developing country. Informatics in Medicine Unlocked 2021;27:100804 View
  3. Bezerra Giordan L, Tong H, Atherton J, Ronto R, Chau J, Kaye D, Shaw T, Chow C, Laranjo L. The Use of Mobile Apps for Heart Failure Self-management: Systematic Review of Experimental and Qualitative Studies. JMIR Cardio 2022;6(1):e33839 View
  4. Plana D, Shung D, Grimshaw A, Saraf A, Sung J, Kann B. Randomized Clinical Trials of Machine Learning Interventions in Health Care. JAMA Network Open 2022;5(9):e2233946 View
  5. Cestari V, Florêncio R, Garces T, Souza L, Negreiros F, Pessoa V, Moreira T. CODESING DE APLICATIVO CUIDATIVO-EDUCACIONAL PARA PESSOAS COM INSUFICIÊNCIA CARDÍACA: IDEAÇÃO, PROTOTIPAGEM E CO-IMPLANTAÇÃO. Texto & Contexto - Enfermagem 2022;31 View
  6. Kalabakov S, Stankoski S, Kiprijanovska I, Andova A, Reščič N, Janko V, Gjoreski M, Gams M, Luštrek M. What Actually Works for Activity Recognition in Scenarios with Significant Domain Shift: Lessons Learned from the 2019 and 2020 Sussex-Huawei Challenges. Sensors 2022;22(10):3613 View
  7. Nourse R, Lobo E, McVicar J, Kensing F, Islam S, Kayser L, Maddison R. Characteristics of Smart Health Ecosystems That Support Self-care Among People With Heart Failure: Scoping Review. JMIR Cardio 2022;6(2):e36773 View
  8. Oyebode O, Fowles J, Steeves D, Orji R. Machine Learning Techniques in Adaptive and Personalized Systems for Health and Wellness. International Journal of Human–Computer Interaction 2023;39(9):1938 View
  9. Lo Z, Harish K, Tan E, Zhu J, Chan S, Liew H, Hoi W, Liang S, Cho Y, Koo H, Wu K, Car J. A feasibility study on the efficacy of a patient-owned wound surveillance system for diabetic foot ulcer care (ePOWS study). DIGITAL HEALTH 2023;9 View
  10. Spaulding E, Isakadze N, Molello N, Khoury S, Gao Y, Young L, Antonsdottir I, Azizi Z, Dorsch M, Golbus J, Ciminelli A, Brant L, Himmelfarb C, Coresh J, Marvel F, Longenecker C, Commodore-Mensah Y, Gilotra N, Sandhu A, Nallamothu B, Martin S. Use of Human-Centered Design Methodology to Develop a Digital Toolkit to Optimize Heart Failure Guideline-Directed Medical Therapy. Journal of Cardiovascular Nursing 2024;39(3):245 View
  11. Mouselimis D, Tsarouchas A, Vassilikos V, Mitsas A, Lazaridis C, Androulakis E, Briasoulis A, Kampaktsis P, Papadopoulos C, Bakogiannis C. The role of patient-oriented mHealth interventions in improving heart failure outcomes: A systematic review of the literature. Hellenic Journal of Cardiology 2024;77:81 View
  12. Kalabakov S, Jovanovski B, Denkovski D, Rakovic V, Pfitzner B, Konak O, Arnrich B, Gjoreski H. Federated Learning for Activity Recognition: A System Level Perspective. IEEE Access 2023;11:64442 View
  13. Wilkens U, Lupp D, Langholf V. Configurations of human-centered AI at work: seven actor-structure engagements in organizations. Frontiers in Artificial Intelligence 2023;6 View
  14. Manga S, Muthavarapu N, Redij R, Baraskar B, Kaur A, Gaddam S, Gopalakrishnan K, Shinde R, Rajagopal A, Samaddar P, Damani D, Shivaram S, Dey S, Mitra D, Roy S, Kulkarni K, Arunachalam S. Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives. Sensors 2023;23(12):5744 View
  15. Boccuto F, De Rosa S, Torella D, Veltri P, Guzzi P. Will Artificial Intelligence Provide Answers to Current Gaps and Needs in Chronic Heart Failure?. Applied Sciences 2023;13(13):7663 View
  16. Bibbo D, De Marchis C, Schmid M, Ranaldi S. Machine learning to detect, stage and classify diseases and their symptoms based on inertial sensor data: a mapping review. Physiological Measurement 2023;44(12):12TR01 View
  17. Martindale A, Llewellyn C, de Visser R, Ng B, Ngai V, Kale A, di Ruffano L, Golub R, Collins G, Moher D, McCradden M, Oakden-Rayner L, Rivera S, Calvert M, Kelly C, Lee C, Yau C, Chan A, Keane P, Beam A, Denniston A, Liu X. Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines. Nature Communications 2024;15(1) View
  18. Gabarron E, Larbi D, Rivera-Romero O, Denecke K. Human Factors in AI-Driven Digital Solutions for Increasing Physical Activity: Scoping Review. JMIR Human Factors 2024;11:e55964 View
  19. Moosavi A, Huang S, Vahabi M, Motamedivafa B, Tian N, Mahmood R, Liu P, Sun C. Prospective Human Validation of Artificial Intelligence Interventions in Cardiology. JACC: Advances 2024;3(9):101202 View
  20. Mooghali M, Stroud A, Yoo D, Barry B, Grimshaw A, Ross J, Zhu X, Miller J. Trustworthy and ethical AI-enabled cardiovascular care: a rapid review. BMC Medical Informatics and Decision Making 2024;24(1) View

Books/Policy Documents

  1. Pavleska S, Rakovic V, Denkovski D, Gjoreski H. Signal Processing Strategies. View