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Intelligent Decision Making for Depression Prevention and Detection based on AHP

Published: 27 March 2019 Publication History

Abstract

Mental disorders are a broad set of problems, with different symptoms, reflecting the existence of dysfunction in the psychological processes, specifically depression is one of the most common psychological disorders and a leading cause of mental disorders the burden of morbidity, especially in patients with cancer, because they are more likely to succumb to the disease, because of the diversity and the multitude of diagnostic criteria, which makes the situation very complex, therefore, decision-making by clinicians will be a very difficult task. In behalf of that the prevention and follow-up of depression trends in cancer patients play a very important role in the quality of their treatment. In this regard, this paper presents the intelligent decision-making framework for automatically monitoring and predicting the level of depression in cancer patients, using the multi-criteria decision-making AHP (Analytic Hierarchy Process) approach, and a data sheet for diagnosis form the Center for Oncology and Hematology of CHU, to extract the main diagnostic criteria, in order to help the clinicians select the best decision, to ensure a better follow up with patients, and reduce the suffering of the disease on their psychology.
This work is carried out in collaboration with the Mohamed VI University Hospital Center of Marrakech in the service of oncology and Hematology.

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Cited By

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  • (2024)Accelerating depression intervention: identifying critical psychological factors using MCDM-MOORA technique for early therapy initiationAnnals of General Psychiatry10.1186/s12991-024-00518-w23:1Online publication date: 9-Oct-2024
  • (2023)TOPSIS for Analyzing the Risk Factors of Suicidal Ideation Among University Students in MalaysiaPertanika Journal of Science and Technology10.47836/pjst.31.2.1731:2(977-994)Online publication date: 6-Mar-2023
  • (2022)Intelligent monitoring for infectious diseases with fuzzy systems and edge computingApplied Soft Computing10.1016/j.asoc.2022.108835123:COnline publication date: 1-Jul-2022

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  1. Intelligent Decision Making for Depression Prevention and Detection based on AHP

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    cover image ACM Other conferences
    NISS '19: Proceedings of the 2nd International Conference on Networking, Information Systems & Security
    March 2019
    512 pages
    ISBN:9781450366458
    DOI:10.1145/3320326
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 27 March 2019

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    Author Tags

    1. AHP
    2. Analytic Hierarchy Process
    3. Depression
    4. decision making

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    View all
    • (2024)Accelerating depression intervention: identifying critical psychological factors using MCDM-MOORA technique for early therapy initiationAnnals of General Psychiatry10.1186/s12991-024-00518-w23:1Online publication date: 9-Oct-2024
    • (2023)TOPSIS for Analyzing the Risk Factors of Suicidal Ideation Among University Students in MalaysiaPertanika Journal of Science and Technology10.47836/pjst.31.2.1731:2(977-994)Online publication date: 6-Mar-2023
    • (2022)Intelligent monitoring for infectious diseases with fuzzy systems and edge computingApplied Soft Computing10.1016/j.asoc.2022.108835123:COnline publication date: 1-Jul-2022

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