According to a new report, published by KBV research, The Global Federated Learning In Healthcare Market size is expected to reach $87.77 Million by 2032, rising at a market growth of 15.5% CAGR during the forecast period.
Several trends are shaping the evolution of federated learning in healthcare market. One notable trend is integrating federated learning with advanced AI techniques, such as transfer and reinforcement learning. These approaches enhance the performance of FL models by allowing them to adapt to new tasks or learn from limited data, making them more effective in healthcare applications like rare disease detection. Another trend is the growing use of federated learning in edge computing.
The On-Premise segment is experiencing a CAGR of 15.1 % during the forecast period. This dominance can be attributed to the preference of many healthcare institutions for maintaining full control over their data infrastructure due to the sensitive nature of patient information and strict regulatory requirements. On-premise deployment allows organizations to manage data security internally, customize system configurations, and integrate federated learning models directly with their existing IT environments.
The Hospitals & Healthcare Providers segment led the maximum revenue in the Global Federated Learning In Healthcare Market by End Use in 2024, thereby, achieving a market value of $35.70 Million by 2032. This is primarily due to the rising need for advanced data analytics to enhance clinical decision-making while ensuring patient privacy. Federated learning enables hospitals to utilize AI-driven insights from distributed patient data without transferring it to a centralized location. It helps improve diagnostics, treatment personalization, and patient outcomes while remaining compliant with privacy regulations like HIPAA.
The Drug Discovery & Development segment is growing at a CAGR of 14.7 % during the forecast period. The need for collaborative data utilization primarily drives this growth without compromising patient privacy. Federated learning enables pharmaceutical companies and research institutions to train machine learning models on decentralized datasets held by different stakeholders.
Full Report: https://www.kbvresearch.com/federated-learning-in-healthcare-market/
The North America region dominated the Global Federated Learning In Healthcare Market by Region in 2024, thereby, achieving a market value of $27.68 Million by 2032. The Europe region is anticipated to grow a CAGR of 15.2% during (2025 - 2032). Additionally, The Asia Pacific region would witness a CAGR of 16.3% during (2025 - 2032).
By Deployment Mode
By End Use
By Application
By Geography
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