The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Deep Learning and Big Data for Biomedical Image Processing in Employee Health: Sparking a Digital Twin in an Era of Lifestyle Upheaval
Abstract
Digital twins emerge as the cornerstone, ushering in an era of personalized healthcare and wellness recommendations. It guides the reader through the intricate network of Big Data and explains its crucial role in the examination of biological images. The foundation of these cutting-edge fields is the creation of digital twins, complex virtual depictions of individual health profiles. This chapter is about improving employees health, advocating for preventative care and providing people with the knowledge and resources they need to take control of their own lives. Simultaneously, it navigates the dynamic IoT ecosystem, revealing its multifaceted contributions to real-time health data acquisition. Deep learning with its neural networks and convolutional prowess, further enhances our understanding and interpretation of biomedical images.
Related Content
|
Jawad Laadraoui, Mehdi Aitlarradia, Khadija Oubella, Fatimzahra Agouram, Sara Oufquir, Abdelfatah Ait Baba, Hamid Kabdy, Bilal El-Mansoury.
© 2026.
40 pages.
|
|
Joselyn Barnhart, Leslie Reyes, Cameron Lacy Ortega.
© 2026.
28 pages.
|
|
Elaine Mora.
© 2026.
30 pages.
|
|
Gabriela Rangel.
© 2026.
32 pages.
|
|
Ayush Dwivedi, Ravindra Singh, Aditya Ratna Tripathi.
© 2026.
24 pages.
|
|
Fathima Yusaira, Papia Saraf, Dakshina U. Kanthy, Lakshmi Balakrishnan, Benita Raj Prince, Diliya Joseph.
© 2026.
30 pages.
|
|
Tiffany Lee, Lyndsay R. Nuyen, Blaire Zielke.
© 2026.
38 pages.
|
|
|