Synergistic Integration of Federated Learning and Visual Intelligence for Disease Diagnosis and Prediction

Abstract

The synergistic integration of federated learning and visual intelligence redefines the next-gen healthcare landscape. Visual intelligence is crucial in disease diagnosis through X-rays, CT and PET scans, MRI, etc. It was enhanced through AI enabled diagnosis systems. These systems are functioning based on centralized and limited training data models. Federated Learning (FL), works among multiple healthcare organizations located at different locations to collaboratively train models without exchanging sensitive patient data, thus maintaining privacy and security. Integrating FL and visual intelligence significantly enhances disease prediction and diagnosis by interpreting medical images on large models. This chapter focuses on the role of technology in next-gen healthcare, FL frameworks, benefits, challenges, and applications; Visual intelligence real-time applications, synergistic integration of FL and vision intelligence in disease prediction use cases of real-time healthcare.

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