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Data Science in Healthcare: COVID-19 and Beyond

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  • Tim Hulsen

    (Department of Hospital Services & Informatics, Philips Research, 5656AE Eindhoven, The Netherlands)

Abstract

Data science is an interdisciplinary field that applies numerous techniques, such as machine learning (ML), neural networks (NN) and artificial intelligence (AI), to create value, based on extracting knowledge and insights from available ‘big’ data [...]

Suggested Citation

  • Tim Hulsen, 2022. "Data Science in Healthcare: COVID-19 and Beyond," IJERPH, MDPI, vol. 19(6), pages 1-4, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:6:p:3499-:d:772074
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    References listed on IDEAS

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    1. Francesco Bellocchio & Caterina Lonati & Jasmine Ion Titapiccolo & Jennifer Nadal & Heike Meiselbach & Matthias Schmid & Barbara Baerthlein & Ulrich Tschulena & Markus Schneider & Ulla T. Schultheiss , 2021. "Validation of a Novel Predictive Algorithm for Kidney Failure in Patients Suffering from Chronic Kidney Disease: The Prognostic Reasoning System for Chronic Kidney Disease (PROGRES-CKD)," IJERPH, MDPI, vol. 18(23), pages 1-18, November.
    2. Abdur Rasool & Chayut Bunterngchit & Luo Tiejian & Md. Ruhul Islam & Qiang Qu & Qingshan Jiang, 2022. "Improved Machine Learning-Based Predictive Models for Breast Cancer Diagnosis," IJERPH, MDPI, vol. 19(6), pages 1-19, March.
    3. Ebtesam Alomari & Iyad Katib & Aiiad Albeshri & Rashid Mehmood, 2021. "COVID-19: Detecting Government Pandemic Measures and Public Concerns from Twitter Arabic Data Using Distributed Machine Learning," IJERPH, MDPI, vol. 18(1), pages 1-34, January.
    4. Yongseok Seo & Seungyeon Lee & Joung-Sook Ahn & Seongho Min & Min-Hyuk Kim & Jang-Young Kim & Dae Ryong Kang & Sangwon Hwang & Phor Vicheka & Jinhee Lee, 2020. "Association of Metabolically Healthy Obesity and Future Depression: Using National Health Insurance System Data in Korea from 2009–2017," IJERPH, MDPI, vol. 18(1), pages 1-9, December.
    5. Ricardo Peralta & Mario Garbelli & Francesco Bellocchio & Pedro Ponce & Stefano Stuard & Maddalena Lodigiani & João Fazendeiro Matos & Raquel Ribeiro & Milind Nikam & Max Botler & Erik Schumacher & Di, 2021. "Development and Validation of a Machine Learning Model Predicting Arteriovenous Fistula Failure in a Large Network of Dialysis Clinics," IJERPH, MDPI, vol. 18(23), pages 1-12, November.
    6. Xialv Lin & Xiaofeng Wang & Yuhan Wang & Xuejie Du & Lizhu Jin & Ming Wan & Hui Ge & Xu Yang, 2021. "Optimized Neural Network Based on Genetic Algorithm to Construct Hand-Foot-and-Mouth Disease Prediction and Early-Warning Model," IJERPH, MDPI, vol. 18(6), pages 1-25, March.
    7. Veronica Rojas-Mendizabal & Cristián Castillo-Olea & Alexandra Gómez-Siono & Clemente Zuñiga, 2021. "Assessment of Thoracic Pain Using Machine Learning: A Case Study from Baja California, Mexico," IJERPH, MDPI, vol. 18(4), pages 1-12, February.
    8. Jennifer Pan & Joseph Marie St. Pierre & Trevor A. Pickering & Natalie L. Demirjian & Brandon K.K. Fields & Bhushan Desai & Ali Gholamrezanezhad, 2020. "Coronavirus Disease 2019 (COVID-19): A Modeling Study of Factors Driving Variation in Case Fatality Rate by Country," IJERPH, MDPI, vol. 17(21), pages 1-11, November.
    9. Shital S. Muke & Deepak Tugnawat & Udita Joshi & Aditya Anand & Azaz Khan & Ritu Shrivastava & Abhishek Singh & Juliana L. Restivo & Anant Bhan & Vikram Patel & John A. Naslund, 2020. "Digital Training for Non-Specialist Health Workers to Deliver a Brief Psychological Treatment for Depression in Primary Care in India: Findings from a Randomized Pilot Study," IJERPH, MDPI, vol. 17(17), pages 1-22, September.
    10. Tim Hulsen, 2020. "Sharing Is Caring—Data Sharing Initiatives in Healthcare," IJERPH, MDPI, vol. 17(9), pages 1-12, April.
    11. Francesco Bellocchio & Paola Carioni & Caterina Lonati & Mario Garbelli & Francisco Martínez-Martínez & Stefano Stuard & Luca Neri, 2021. "Enhanced Sentinel Surveillance System for COVID-19 Outbreak Prediction in a Large European Dialysis Clinics Network," IJERPH, MDPI, vol. 18(18), pages 1-18, September.
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    Cited by:

    1. François Bocquet & Mario Campone & Marc Cuggia, 2022. "The Challenges of Implementing Comprehensive Clinical Data Warehouses in Hospitals," IJERPH, MDPI, vol. 19(12), pages 1-6, June.

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