Preparation and Challenges in Developing a Big Data Analysis Framework in Occupational Medicine in Indonesia

Author:

KEKALIH Aria1,ADI Nuri Purwito12,SOEMARKO Dewi Sumaryani1

Affiliation:

1. Department of Community Medicine, Faculty of Medicine, Universitas Indonesia

2. Department of Occupational Health Practice and Management, Institute of Industrial and Ecological Sciences, University of Occupational and Environmental Health, Japan.

Publisher

The University of Occupational and Environmental Health, Japan

Reference22 articles.

1. 1 . Ministry of Foreign Affairs of The Republic of Indonesia (2023): Industrial Diplomacy: Towards Indonesia 4.0 via Hannover Messe 2023. https://kemlu.go.id/portal/en/read/4642/berita/industrial-diplomacy-towards-indonesia-40-via-hannover-messe-2023 (acccessed December 21, 2023)

2. 2 . Jagatheesaperumal SK, Rahouti M, Ahmad K, Al-Fuqaha A & Guizani M (2022): The duo of artificial intelligence and big data for industry 4.0: Applications, techniques, challenges, and future research directions. IEEE Internet of Things J 9 (15): 12861−12885

3. 3 . Deshpande A & Kumar M (2018): Artificial intelligence for big data : complete guide to automating big data solutions using artificial intelligence techniques. Packt Publishing Birmingham, Birmingham 371pp

4. 4 . Mooney SJ & Pejaver V (2018): Big data in public health: terminology, machine learning, and privacy. Annu Rev Public Health 39: 95−112

5. 5 . Brodie MA, Pliner EM, Ho A et al (2018): Big data vs accurate data in health research: Large-scale physical activity monitoring, smartphones, wearable devices and risk of unconscious bias. Med Hypotheses 119: 32−36

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