# Federated Learning * **Definition:** Federated Learning is a decentralized machine learning approach that enables multiple healthcare institutions to collaboratively train a shared model on their local data without exchanging sensitive patient information, thereby enhancing privacy and security while leveraging diverse datasets to improve predictive accuracy and clinical outcomes. * **Taxonomy:** CTO Topics / Federated Learning ## News * Selected news on the topic of **Federated Learning**, for healthcare technology leaders * 529 news items are in the system for this topic * Posts have been filtered for tech and healthcare-related keywords | Date | Title | Source | | --- | --- | --- | | 5/21/2025 | [**AI in Healthcare: Predictive Analytics & AI-Assisted Diagnoses - LinkedIn**](https://www.linkedin.com/pulse/ai-healthcare-predictive-analytics-ai-assisted-aex6c) | [[Linkedin]] | | 5/8/2025 | [**Revolutionizing AI: How FLock.io Is Expanding Global Decentralized Solutions**](https://finance.yahoo.com/news/revolutionizing-ai-flock-io-expanding-124000904.html) | [[Yahoo Finance]] | | 2/27/2025 | [**Philips Champions Digital Transformation at BioAsia 2025 - ICT&health International**](https://ictandhealth.com/ai-health-news/philips-champions-digital-transformation-at-bioasia-2025) | [[ICT and Health]] | | 2/24/2025 | [**The need for secure data sharing: Lessons learned from public health - Computer Weekly**](https://www.computerweekly.com/opinion/The-need-for-secure-data-sharing-Lessons-learned-from-public-health) | [[Computer Weekly]] | | 2/12/2025 | [**Catalysts Of Change: Leadership's Role In Pharma Data Science Innovation**](https://www.forbes.com/councils/forbestechcouncil/2025/02/13/catalysts-of-change-leaderships-role-in-pharma-data-science-innovation/) | [[Forbes]] | | 1/19/2025 | [**NVIDIA Clara: Transforming Healthcare with AI-Powered Innovations - Medium**](https://medium.com/the-ai-entrepreneurs/nvidia-clara-transforming-healthcare-with-ai-powered-innovations-448617c90b52) | [[Medium]] | | 12/20/2024 | [**Collaboration will be key to transform healthcare with AI - The World Economic Forum**](https://www.weforum.org/stories/2024/12/improving-healthcare-in-the-intelligent-age-requires-cultural-change-and-collaboration/) | [[World Economic Forum]] | | 12/15/2024 | [**The Future of AI in Drug Development - by Kayden Break - Operations Research Bit**](https://medium.com/operations-research-bit/the-future-of-ai-in-drug-development-463121a2e30d) | [[Medium]] | | 12/5/2024 | [**What's next in AI's drug discovery journey**](https://www.fiercepharma.com/sponsored/whats-next-ais-drug-discovery-journey-0) | [[FiercePharma]] | | 11/25/2024 | [**What's next in AI's drug discovery journey**](https://www.fiercebiotech.com/sponsored/whats-next-ais-drug-discovery-journey) | [[FierceBiotech]] | | 11/18/2024 | [**generative ai in healthcare: coding the future of medicine - by TEJESWAR REDDY - Medium**](https://medium.com/@tejeswar_79802/generative-ai-in-healthcare-coding-the-future-of-medicine-b83eb4108287) | [[Medium]] | | 11/8/2024 | [**WiMi Researches Reinforcement Learning-Based Blockchain Federated Learning ... - PR Newswire**](https://www.prnewswire.com/news-releases/wimi-researches-reinforcement-learning-based-blockchain-federated-learning-framework-to-optimize-model-aggregation-strategy-and-security-302300038.html) | [[PR Newswire]] | | 11/1/2024 | [**WiMi is Working on a Blockchain-Enhanced Federal Learning Privacy-Preserving Mechanism**](https://www.prnewswire.com/news-releases/wimi-is-working-on-a-blockchain-enhanced-federal-learning-privacy-preserving-mechanism-302294207.html) | [[PR Newswire]] | | 10/7/2024 | [**Beyond the clinic: How Korean IT giants spur digital health evolution - Healthcare IT News**](https://www.healthcareitnews.com/news/asia/beyond-clinic-how-korean-it-giants-spur-digital-health-evolution) | [[Healthcare IT News]] | | 9/22/2024 | [**Medical Experts Utilize NVIDIA-Powered Federated Learning to Advance AI in Tumor Segmentation**](https://hitconsultant.net/2024/09/23/medical-experts-utilize-nvidia-powered-federated-learning/) | [[HIT Consultant]] | | 9/19/2024 | [**Nitin Kumar, VP of Healthcare at TCS, Examines the Security Risks of Wearable Health Devices**](https://healthcare-digital.com/medical-devices-and-pharma/tcs-nitin-kumar-on-the-security-of-wearable-devices) | healthcare-digital.com | | 9/9/2024 | [**WiMi Developed a Blockchain Empowered Asynchronous Federated Learning for ... - PR Newswire**](https://www.prnewswire.com/news-releases/wimi-developed-a-blockchain-empowered-asynchronous-federated-learning-for-optimizing-model-training-302242119.html) | [[PR Newswire]] | | 9/5/2024 | [**Lucinity Secures Patent for Federated Learning AI, Enabling Secure Data Sharing - PR Newswire**](https://www.prnewswire.com/news-releases/lucinity-secures-patent-for-federated-learning-ai-enabling-secure-data-sharing-302238521.html) | [[PR Newswire]] | | 8/19/2024 | [**Harnessing AI, Federated Learning And Blockchain For A Better Future In Medical Use Cases**](https://www.forbes.com/councils/forbestechcouncil/2024/08/20/harnessing-ai-federated-learning-and-blockchain-for-a-better-future-in-medical-use-cases/) | [[Forbes]] | | 8/5/2024 | [**NIIMBL announces 2 RFIs focused on data connectivity and federated learning for ... - PR Newswire**](https://www.prnewswire.com/news-releases/niimbl-announces-2-rfis-focused-on-data-connectivity-and-federated-learning-for-biopharmaceutical-manufacturing-302213674.html) | [[PR Newswire]] | | 7/26/2024 | [**WiMi Built an Advanced Data Structure Architecture Using Homomorphic Encryption and ...**](https://www.prnewswire.com/news-releases/wimi-built-an-advanced-data-structure-architecture-using-homomorphic-encryption-and-federated-learning-302207432.html) | [[PR Newswire]] | | 7/17/2024 | [**Data Privacy in Healthcare: Balancing Innovation with Patient Security**](https://www.healthcareittoday.com/2024/07/17/data-privacy-in-healthcare-balancing-innovation-with-patient-security/) | [[Healthcare IT Today]] | | 7/3/2024 | [**Cloud-magnetic resonance imaging system in the 6G and AI era - Medical Xpress**](https://medicalxpress.com/news/2024-07-cloud-magnetic-resonance-imaging-6g.html) | [[MedicalXpress]] | | 12/19/2023 | [**Levelling the playing field: Could a UK cloud strategy weaken the hold of the hyperscalers?**](https://www.computerweekly.com/feature/Levelling-the-playing-field-Could-a-UK-cloud-strategy-weaken-the-hold-of-the-hyperscalers) | [[Computer Weekly]] | | 9/19/2022 | [**DynamoFL aims to bring privacy-preserving AI to more industries**](https://techcrunch.com/2022/09/20/dynamofl-aims-to-bring-privacy-preserving-ai-to-more-industries/) | [[TechCrunch]] | ## Topic Overview (Some LLM-derived content — please confirm with above primary sources) ### Key Players - **Google**: Proposed federated learning in 2016 to enable model training without transferring original data samples. - **Rhino Federated Computing**: Partnering with Flower to enhance access to federated learning technologies. - **Google Cloud**: Partnering with Swift to create privacy-preserving solutions using federated learning. - **Flower**: An open-source federated learning framework that Rhino is integrating into its platform. - **Lucinity**: A company that has patented federated learning technology for secure data sharing in financial systems. - **Swift**: A financial services organization collaborating with Google Cloud to enhance fraud detection using federated learning. - **WiMi Hologram Cloud Inc.**: A company developing blockchain-based federated learning frameworks to enhance data privacy and model training efficiency. - **NVIDIA**: A technology company providing federated learning solutions, particularly in medical imaging and AI model development. - **NVIDIA Clara**: An AI-powered platform enhancing healthcare applications, including federated learning capabilities. - **Texas A&M Health**: An institution utilizing federated learning and blockchain technologies to improve clinical research and patient privacy. - **National Institute for Innovation in Manufacturing Biopharmaceuticals (NIIMBL)**: A key organization promoting data-driven innovation in biopharmaceutical manufacturing, focusing on federated learning and universal connectivity. - **Vaultree**: A company that has developed the VENum framework for secure machine learning on encrypted data. - **Avandra**: The world's largest federated network for medical imaging and clinical data, focused on improving patient care. - **Diliko**: Recognized for its Agentic AI platform that automates data workflows and ensures security in regulated industries. - **Tevogen Bio**: Utilizes AI and machine learning for developing T-cell therapeutics, emphasizing patient equity. - **Avant Technologies, Inc.**: A company focused on enhancing data security and privacy for AI-driven healthcare applications. - **Baird Medical**: Developed an AI Tumor Ablation Surgical Robot, showcasing advancements in AI and robotics in medicine. - **Cancer AI Alliance (CAIA)**: A collaboration of National Cancer Institute-designated cancer centers and AI technology companies to advance cancer research. - **Accenture**: A consulting firm investing in 1910 Genetics to enhance drug discovery using AI. ### Partnerships and Collaborations - **Rhino Federated Computing and Flower**: Enhancing enterprise access to federated learning technologies. - **Google Cloud and Swift**: Creating a secure solution for financial institutions using federated learning. - **Society for Imaging Informatics and Medicine (SIIM)**: Leading a project utilizing NVIDIA FLARE technology for federated learning among multiple medical centers. - **Avandra and Datavant**: Integrating federated networks to enhance secure health data exchange. - **Cancer AI Alliance**: Formed by leading cancer centers and AI companies to leverage collective data for cancer research while ensuring data security. - **Texas A&M Health and BurstIQ**: Collaborating to enhance clinical research through improved data management and patient privacy using the LifeGraph platform. - **Tevogen Bio and Microsoft**: Collaboration to leverage AI-driven modeling for drug candidate identification. - **Accenture and 1910 Genetics**: Working together to improve drug discovery processes through AI. - **EU Horizon Programme**: Supports collaborative projects like RES-Q+ to improve stroke patient care globally. ### Innovations, Trends, and Initiatives - **Federated Learning**: A privacy-preserving machine learning approach that allows models to be trained across decentralized data sources without sharing sensitive patient data. - **Clustered Federated Learning (CFL)**: Aims to create specialized global models for similar user groups to improve adaptability. - **Privacy-Preserving Federated Learning (PPFL)**: An emerging trend that combines federated learning with privacy-enhancing technologies to protect patient data. - **Hybrid Model Federated Learning**: NIIMBL's initiative requesting innovative approaches to integrate federated learning with hybrid models for biopharmaceutical manufacturing. - **Blockchain-based Asynchronous Federated Learning (BAFL)**: WiMi's framework combining blockchain technology with federated learning to enhance model training efficiency and security. - **Generative AI in Healthcare**: Emerging trend utilizing federated learning to create synthetic datasets and improve patient care while addressing data privacy concerns. - **NVIDIA Clara**: Utilizing federated learning to enhance AI applications in healthcare, including drug discovery and medical imaging. - **Avandra's Federated Network**: Aiming to create a comprehensive ecosystem for medical imaging data to improve research and patient care. - **Resource-Adaptive Framework**: Proposed to ensure fair participation and improve model accuracy while safeguarding patient privacy. - **Privacy-Enhancing Technologies (PETs)**: Technologies that enable secure data sharing among healthcare organizations, crucial for collaboration and innovation. - **AI in Drug Discovery**: The integration of AI in drug discovery processes is transforming traditional R&D, enhancing efficiency and reducing costs. ### Challenges and Concerns - **Data Privacy and Security**: Federated learning addresses privacy concerns by allowing model training on decentralized data without sharing raw data, but challenges remain in ensuring data integrity and compliance. - **Data Privacy**: Federated learning addresses privacy concerns but highlights disparities in resource access among institutions. - **Inefficient Communication**: Federated learning faces challenges such as slow convergence and communication inefficiencies, particularly with large decentralized datasets. - **Data Heterogeneity**: Variations in data quality and availability can affect the performance of federated learning models. - **Regulatory Compliance**: Healthcare organizations face challenges in adhering to strict regulations while implementing federated learning technologies. - **Scalability**: The need for scalable solutions in federated learning to accommodate large datasets and diverse healthcare applications. - **Algorithmic Bias**: The need for diverse and representative data in federated learning to mitigate biases in AI models and ensure equitable healthcare outcomes. - **Fragmented Data Ecosystem**: The disjointed nature of healthcare data creates vulnerabilities that can be exploited by cybercriminals, highlighting the need for comprehensive security frameworks.