The success of deep learning (DL) relies heavily on training data from which DL models encapsulate information. Consequently, the development and deployment of DL models expose data to potential privacy breaches, which are particularly…
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Ethical Concerns, Privacy Issues and Lack of Trust in AI
BSI’s International AI Maturity Model was developed to assess readiness for advanced AI adoption. Healthcare scored lowest in terms of maturity over seven sectors, with…
Privacy and data usage in the age of artificial intelligence are colliding in healthcare where maintaining trust is as essential as advancing patient care. Secure encryption technologies and regulatory guidance can help to ensure…
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Epic asks a federal court to dismiss the antitrust lawsuit that Particle Health brought against it, citing these arguments:
Particle’s customers violated patient privacy by accessing records for non-treatment purposes and Epic says that…
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As the healthcare industry increasingly adopts AI, the landscape of cybersecurity threats is changing rapidly. While AI can enhance patient care and streamline operations, it also introduces new vulnerabilities that cybercriminals may exploit.To help…
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Sarah Danielson, MS, MBA, CPDHTS, CDH-L, FACHDM, Sr Director, Strategy & Advisory, Health Solutions Group atTrace3
With healthcare data breaches on the rise and concerns about patient privacy escalating, the role of AI in anomaly…
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Robust data privacy regulations hinder the exchange of healthcare data among institutions, crucial for global insights and developing generalised clinical models. Federated learning (FL) is ideal for training global models using datasets from different…
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Selfii, a company that provides privacy-preserving health data, announced it is partnering with secure identity company CLEAR to streamline and strengthen patient access to health records via Selfii’s patient data network.The aim of the…
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In multicentric studies, data sharing between institutions might negatively impact patient privacy or data security. An alternative is federated analysis by secure multiparty computation. This pilot study demonstrates an architecture and implementation addressing both…
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Privacy, systems interoperability, and lack of research capability are some of the biggest challenges in utilising big data for national precision medicine projects in advanced health systems in Asia.Health leaders from Taiwan, South Korea, and…
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