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  • 1
    In: JMIR Research Protocols, JMIR Publications Inc., Vol. 12 ( 2023-4-21), p. e45475-
    Abstract: According to Europe’s Beating Cancer Plan, the number of cancer survivors is growing every year and is now estimated at over 12 million in Europe. A main objective of the European Commission is to ensure that cancer survivors can enjoy a high quality of life, underlining the role of digital technology and eHealth apps and tools to achieve this. Objective The main objective of this study is the development of a user-centered artificial intelligence system to facilitate the input and integration of patient-related biopsychosocial data to improve posttreatment quality of life, well-being, and health outcomes and examine the feasibility of this digitally assisted workflow in a real-life setting in patients with colorectal cancer and acute myeloid leukemia. Methods A total of 60 patients with colorectal cancer and 30 patients with acute myeloid leukemia will be recruited from 2 clinical centers: Universitätsmedizin der Johannes Gutenberg-Universität Mainz (Mainz, Germany) and IRCCS Istituto Romagnolo per lo Studio dei Tumori “Dino Amadori” (IRST, Italy). Psychosocial data (eg, emotional distress, fatigue, quality of life, subjective well-being, sleep problems, and appetite loss) will be collected by questionnaires via a smartphone app, and physiological data (eg, heart rate, skin temperature, and movement through step count) will be collected by a customizable smart wrist-worn sensor device. Each patient will be assessed every 2 weeks over their 3-month participation in the ONCORELIEF study. Inclusion criteria include patients with the diagnosis of acute myeloid leukemia or colorectal cancer, adult patients aged 18 years and older, life expectancy greater than 12 months, Eastern Cooperative Oncology Group performance status ≤2, and patients who have a smartphone and agree to use it for the purpose of the study. Exclusion criteria include patients with a reduced cognitive function (such as dementia) or technological illiteracy and other known active malignant neoplastic diseases (patients with a medical history of treated neoplastic disease are included). Results The pilot study started on September 1, 2022. As of January 2023, we enrolled 33 patients with colorectal cancer and 7 patients with acute myeloid leukemia. As of January 2023, we have not yet started the data analysis. We expect to get all data in June 2023 and expect the results to be published in the second semester of 2023. Conclusions Web-based and mobile apps use methods from mathematical decision support and artificial intelligence through a closed-loop workflow that connects health professionals and patients. The ONCORELIEF system has the potential of continuously identifying, collecting, and processing data from diverse patient dimensions to offer health care recommendations, support patients with cancer to address their unmet needs, and optimize survivorship care. Trial Registration German Clinical Trials Register (DRKS) 00027808; https://drks.de/search/en/trial/DRKS00027808 International Registered Report Identifier (IRRID) DERR1-10.2196/45475
    Type of Medium: Online Resource
    ISSN: 1929-0748
    Language: English
    Publisher: JMIR Publications Inc.
    Publication Date: 2023
    detail.hit.zdb_id: 2719222-2
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  • 2
    In: Neural Computing and Applications, Springer Science and Business Media LLC, Vol. 35, No. 29 ( 2023-10), p. 21381-21397
    Abstract: This publication presents a solution approach to oncological aftercare for cancer patients by means of artificial intelligence (AI) methods. This approach shall support patients in overcoming the after-effects of therapy effectively with suitable supportive actions and health-care professionals in goal-oriented planning of these actions. Different AI methods are used for analyzing patients’ needs for supportive actions depending on the available health data and for a monitoring of these actions. Decision support methods are used for effective planning of actions based on the AI results of analysis. The solution approach is realized in the form of a web application for health-care professionals, which allows for data analysis and planning of actions, and a mobile application for patients, which facilitates documentation and monitoring of supportive actions. In combination, they facilitate a closed-loop workflow for the effective cooperation of health-care professionals and cancer patients. The solution approach is illustrated for an exemplary case scenario of colorectal cancer.
    Type of Medium: Online Resource
    ISSN: 0941-0643 , 1433-3058
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 1136944-9
    detail.hit.zdb_id: 1480526-1
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