Abstract:
The Now a days, Terahertz (THz) imaging can be
used to improve healthcare in several ways. Firstly, THz imaging
can be used for cancer detection, allowing for early detection
before visible symptoms appear. THz imaging can distinguish
between healthy tissue and cancerous tissue, providing sharper
imaging and molecular fingerprinting. Furthermore, THz
imaging can be integrated with artificial intelligence, internet of
things, cloud computing, and big data analytics to create more
sophisticated healthcare systems. Split learning is a privacypreserving
method that collectively with deep learning method
used in the healthcare system to train collaborative models
without sharing raw patient data between clients. Split learning
algorithms, occur when training models sequentially, making
them more robust and effective. Multi-site split learning is a
novel algorithm that enables secure data transfer between
hospitals, ensuring privacy while achieving optimal performance.
To full fill this objective here we have review various THz
technology on the healthcare system and introduced a machine
learning with a split learning based secured method, that has the
potential to revolutionize healthcare by enabling early detection,
improving diagnostics, and facilitating personalized treatment
approaches. The article also associate with various review
algorithm’s potential impact on compact and portable consumer
devices, such as smartphones and wearable health trackers,
which may applicable on real life.
