IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i6p3313-d769640.html
   My bibliography  Save this article

Musawah: A Data-Driven AI Approach and Tool to Co-Create Healthcare Services with a Case Study on Cancer Disease in Saudi Arabia

Author

Listed:
  • Nala Alahmari

    (Department of Computer Science, FCIT, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Sarah Alswedani

    (Department of Computer Science, FCIT, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Ahmed Alzahrani

    (Department of Computer Science, FCIT, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Iyad Katib

    (Department of Computer Science, FCIT, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Aiiad Albeshri

    (Department of Computer Science, FCIT, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Rashid Mehmood

    (High-Performance Computing Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

The sustainability of human existence is in dire danger and this threat applies to our environment, societies, and economies. Smartization of cities and societies has the potential to unite individuals and nations towards sustainability as it requires engaging with our environments, analyzing them, and making sustainable decisions regulated by triple bottom line (TBL). Poor healthcare systems affect individuals, societies, the planet, and economies. This paper proposes a data-driven artificial intelligence (AI) based approach called Musawah to automatically discover healthcare services that can be developed or co-created by various stakeholders using social media analysis. The case study focuses on cancer disease in Saudi Arabia using Twitter data in the Arabic language. Specifically, we discover 17 services using machine learning from Twitter data using the Latent Dirichlet Allocation algorithm (LDA) and group them into five macro-services, namely, Prevention, Treatment, Psychological Support, Socioeconomic Sustainability, and Information Availability. Subsequently, we show the possibility of finding additional services by employing a topical search over the dataset and have discovered 42 additional services. We developed a software tool from scratch for this work that implements a complete machine learning pipeline using a dataset containing over 1.35 million tweets we curated during September–November 2021. Open service and value healthcare systems based on freely available information can revolutionize healthcare in manners similar to the open-source revolution by using information made available by the public, the government, third and fourth sectors, or others, allowing new forms of preventions, cures, treatments, and support structures.

Suggested Citation

  • Nala Alahmari & Sarah Alswedani & Ahmed Alzahrani & Iyad Katib & Aiiad Albeshri & Rashid Mehmood, 2022. "Musawah: A Data-Driven AI Approach and Tool to Co-Create Healthcare Services with a Case Study on Cancer Disease in Saudi Arabia," Sustainability, MDPI, vol. 14(6), pages 1-41, March.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3313-:d:769640
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/6/3313/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/6/3313/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Matthew J Eckelman & Jodi Sherman, 2016. "Environmental Impacts of the U.S. Health Care System and Effects on Public Health," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-14, June.
    2. Tan Yigitcanlar & Rashid Mehmood & Juan M. Corchado, 2021. "Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    3. Tan Yigitcanlar & Massimo Regona & Nayomi Kankanamge & Rashid Mehmood & Justin D’Costa & Samuel Lindsay & Scott Nelson & Adiam Brhane, 2022. "Detecting Natural Hazard-Related Disaster Impacts with Social Media Analytics: The Case of Australian States and Territories," Sustainability, MDPI, vol. 14(2), pages 1-23, January.
    4. Mortenson, Michael J. & Vidgen, Richard, 2016. "A computational literature review of the technology acceptance model," International Journal of Information Management, Elsevier, vol. 36(6), pages 1248-1259.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ghadah Alkhayat & Syed Hamid Hasan & Rashid Mehmood, 2022. "SENERGY: A Novel Deep Learning-Based Auto-Selective Approach and Tool for Solar Energy Forecasting," Energies, MDPI, vol. 15(18), pages 1-55, September.
    2. Eman Alqahtani & Nourah Janbi & Sanaa Sharaf & Rashid Mehmood, 2022. "Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling," Sustainability, MDPI, vol. 14(20), pages 1-65, October.
    3. Ali Khosravi Kazazi & Fariba Amiri & Yaser Rahmani & Raheleh Samouei & Hamidreza Rabiei-Dastjerdi, 2022. "A New Hybrid Model for Mapping Spatial Accessibility to Healthcare Services Using Machine Learning Methods," Sustainability, MDPI, vol. 14(21), pages 1-18, October.
    4. Raniah Alsahafi & Ahmed Alzahrani & Rashid Mehmood, 2023. "Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations," Sustainability, MDPI, vol. 15(5), pages 1-64, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Istiak Ahmad & Fahad Alqurashi & Ehab Abozinadah & Rashid Mehmood, 2022. "Deep Journalism and DeepJournal V1.0: A Data-Driven Deep Learning Approach to Discover Parameters for Transportation," Sustainability, MDPI, vol. 14(9), pages 1-72, May.
    2. Eman Alqahtani & Nourah Janbi & Sanaa Sharaf & Rashid Mehmood, 2022. "Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling," Sustainability, MDPI, vol. 14(20), pages 1-65, October.
    3. Baillette, Paméla & Barlette, Yves & Leclercq-Vandelannoitte, Aurélie, 2018. "Bring your own device in organizations: Extending the reversed IT adoption logic to security paradoxes for CEOs and end users," International Journal of Information Management, Elsevier, vol. 43(C), pages 76-84.
    4. Queiroz, Maciel M. & Fosso Wamba, Samuel, 2019. "Blockchain adoption challenges in supply chain: An empirical investigation of the main drivers in India and the USA," International Journal of Information Management, Elsevier, vol. 46(C), pages 70-82.
    5. Raniah Alsahafi & Ahmed Alzahrani & Rashid Mehmood, 2023. "Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations," Sustainability, MDPI, vol. 15(5), pages 1-64, February.
    6. Manfred Lenzen & Mengyu Li & Arunima Malik & Francesco Pomponi & Ya-Yen Sun & Thomas Wiedmann & Futu Faturay & Jacob Fry & Blanca Gallego & Arne Geschke & Jorge Gómez-Paredes & Keiichiro Kanemoto & St, 2020. "Global socio-economic losses and environmental gains from the Coronavirus pandemic," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-13, July.
    7. Renata Walczak & Magdalena Kludacz-Alessandri & Liliana Hawrysz, 2022. "Use of Telemedicine Technology among General Practitioners during COVID-19: A Modified Technology Acceptance Model Study in Poland," IJERPH, MDPI, vol. 19(17), pages 1-18, September.
    8. Włodzimierz Kanownik & Agnieszka Policht-Latawiec & Wioletta Fudała, 2019. "Nutrient Pollutants in Surface Water—Assessing Trends in Drinking Water Resource Quality for a Regional City in Central Europe," Sustainability, MDPI, vol. 11(7), pages 1-15, April.
    9. Gupta, Ashish & Li, Han & Farnoush, Alireza & Jiang, Wenting, 2022. "Understanding patterns of COVID infodemic: A systematic and pragmatic approach to curb fake news," Journal of Business Research, Elsevier, vol. 140(C), pages 670-683.
    10. Ligorio, Lorenzo & Venturelli, Andrea & Caputo, Fabio, 2022. "Tracing the boundaries between sustainable cities and cities for sustainable development. An LDA analysis of management studies," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    11. Kris Hartley, 2023. "Public Perceptions About Smart Cities: Governance and Quality-of-Life in Hong Kong," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 731-753, April.
    12. Weiwei Mo & Darline Balen & Marianna Moura & Kevin H. Gardner, 2018. "A Regional Analysis of the Life Cycle Environmental and Economic Tradeoffs of Different Economic Growth Paths," Sustainability, MDPI, vol. 10(2), pages 1-16, February.
    13. Peng Jiang & Jiří Jaromír Klemeš & Yee Van Fan & Xiuju Fu & Yong Mong Bee, 2021. "More Is Not Enough: A Deeper Understanding of the COVID-19 Impacts on Healthcare, Energy and Environment Is Crucial," IJERPH, MDPI, vol. 18(2), pages 1-22, January.
    14. Amy Booth, 2022. "Carbon footprint modelling of national health systems: Opportunities, challenges and recommendations," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(4), pages 1885-1893, July.
    15. Christian WEISMAYER, 2022. "Applied Research in Quality of Life: A Computational Literature Review," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(3), pages 1433-1458, June.
    16. Tao Li & Junlin Zhu & Jianqiang Luo & Chaonan Yi & Baoqing Zhu, 2023. "Breaking Triopoly to Achieve Sustainable Smart Digital Infrastructure Based on Open-Source Diffusion Using Government–Platform–User Evolutionary Game," Sustainability, MDPI, vol. 15(19), pages 1-24, October.
    17. Esteban A. Soto & Andrea Hernandez-Guzman & Alexander Vizcarrondo-Ortega & Amaya McNealey & Lisa B. Bosman, 2022. "Solar Energy Implementation for Health-Care Facilities in Developing and Underdeveloped Countries: Overview, Opportunities, and Challenges," Energies, MDPI, vol. 15(22), pages 1-17, November.
    18. Masoumeh Vali & Khodakaram Salimifard & Amir H. Gandomi & Thierry J. Chaussalet, 2022. "Care process optimization in a cardiovascular hospital: an integration of simulation–optimization and data mining," Annals of Operations Research, Springer, vol. 318(1), pages 685-712, November.
    19. Jieyin Lyu & Shouqin Zhou & Jingang Liu & Bingchun Jiang, 2023. "Intelligent-Technology-Empowered Active Emergency Command Strategy for Urban Hazardous Chemical Disaster Management," Sustainability, MDPI, vol. 15(19), pages 1-28, September.
    20. Muhammad Asgher Nadeem & Scott Uk-Jin Lee & Muhammad Usman Younus, 2022. "A Comparison of Recent Requirements Gathering and Management Tools in Requirements Engineering for IoT-Enabled Sustainable Cities," Sustainability, MDPI, vol. 14(4), pages 1-18, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3313-:d:769640. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.