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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Laymouna, M., Ma, Y., Lessard, D., Engler, K., Therrien, R., Schuster, T., Vicente, S., Achiche, S., Haj, M. N. E., Lemire, B., Kawaiah, A., & Lebouché, B. (2024). Needs-assessment for an artificial intelligence-based Chatbot for pharmacists in HIV care: results from a knowledge–attitudes–practices survey. Healthcare, 12(16), 1661-1661. Available
Ma, Y., Achiche, S., Pomey, M.-P., Paquette, J., Adjtoutah, N., Vicente, S., Engler, K., Laymouna, M., Lessard, D., Lemire, B., Asselah, J., Therrien, R., Osmanlliu, E., Zawati, M. H., Joly, Y., & Lebouché, B. (2024). Adapting and Evaluating an AI-Based Chatbot Through Patient and Stakeholder Engagement to Provide Information for Different Health Conditions: Master Protocol for an Adaptive Platform Trial (the MARVIN Chatbots Study). JMIR Research Protocols, 13, 54668. External link
Ma, Y., Achiche, S., Tu, G., Vicente, S., Lessard, D., Engler, K., Lemire, B., chatbots Patient Expert Committee, M. A. R. V. I. N., Laymouna, M., de Pokomandy, A., Cox, J., & Lebouché, B. (2024). The first AI-based Chatbot to promote HIV self-management: A mixed methods usability study. HIV Medicine, 13720 (23 pages). External link
Ma, Y., Lessard, D., Vicente, S., Engler, K., Rodriguez Cruz, A., Laymouna, M., Hijal, T., Del Balso, L., Thériault, G., Paisible, N., Kronfli, N., Pomey, M.-P., Peiris, H., Barkati, S., Brouillette, M.-J., Klein, M., Cox, J., de Pokomandy, A., Asselah, J., ... Lebouché, B. (2024). Implementing a Patient Portal for the Remote Follow-Up of Self-Isolating Patients With COVID-19 Infection Through Patient and Stakeholder Engagement (the Opal-COVID Study): Mixed Methods Pilot Study. Journal of Participatory Medicine, 16. External link
Lessard, D., Engler, K., Ma, Y., Rodriguez Cruz, A., Vicente, S., Kronfli, N., Barkati, S., Brouillette, M.-J., Cox, J., Kildea, J., Hijal, T., Pomey, M.-P., Bartlett, S. J., Asselah, J., & Lebouché, B. (2022). Remote follow-up of self-isolating COVID-19 patients with a patient portal: Protocol for a mixed-method pilot study (the Opal-COVID study). JMIR Res Protoc, 18(11). External link
Engler, K., Vicente, S., Ma, Y., Hijal, T., Cox, J., Ahmed, S., Klein, M., Achiche, S., Pant Pai, N., de Pokomandy, A., Lacombe, K., & Lebouché, B. (2021). Implementation of an electronic patient-reported measure of barriers to antiretroviral therapy adherence with the Opal patient portal: Protocol for a mixed method type 3 hybrid pilot study at a large Montreal HIV clinic. PLOS ONE, 16(12), 19 pages. External link
