Medical information security in the era of artificial intelligence

Core Legal Challenges for Medical 3D Printing in the EU

3D printing has been adopted into routine use for certain medical applications, but more widespread usage has been hindered by, among other things, unclear legislation. We performed an analysis, using legal doctrinal study and legal informatics, of relevant EU legislation and case law in four issues relevant to medical 3D printing (excluding bioprinting or pharmacoprinting): pre-market approval, post-market liability, intellectual property rights, and data protection. Several gaps and uncertainties in the current legislation and interpretations were identified. In particular, we regard the current EU regulatory framework to be quite limiting and inflexible, exemplifying a cautionary approach common in EU law. Though the need to establish high safety standards in order to protect patients as a disadvantaged population is understood, both legal uncertainties and overregulation are seen as harmful to innovation. Hence, more adaptive legislation is called for to ensure continuous innovation efforts and enhanced patient outcomes.

Legal issues and underexplored data protection in medical 3D printing: A scoping review

Introduction: 3D printing has quickly found many applications in medicine. However, as with any new technology the regulatory landscape is struggling to stay abreast. Unclear legislation or lack of legislation has been suggested as being one hindrance for wide-scale adoption. Methods: A scoping review was performed in PubMed, Web of Science, SCOPUS and Westlaw International to identify articles dealing with legal issues in medical 3D printing. Results: Thirty-four articles fulfilling inclusion criteria were identified in medical/technical databases and fifteen in the legal database. The majority of articles dealt with the USA, while the EU was also prominently represented. Some common unresolved legal issues were identified, among them terminological confusion between custom-made and patient-matched devices, lack of specific legislation for patient-matched products, and the undefined legal role of CAD files both from a liability and from an intellectual property standpoint. Data protection was mentioned only in two papers and seems an underexplored topic. Conclusion: In this scoping review, several relevant articles and several common unresolved legal issues were identified including a need for terminological uniformity in medical 3D printing. The results of this work are planned to inform our own deeper legal analysis of these issues in the future.

A robust encryption watermarking algorithm for medical images based on ridgelet-DCT and THM double chaos

With the help of big data, cloud computing, artificial intelligence and other technologies, the informatization and intelligence of the wisdom medical have been gradually realized. However, with the transmission and storage of massive amounts of medical images in the cloud, information security issues have become increasingly prominent. The privacy of patients is at risk of disclosure, theft and tampering, which has become an important challenge restricting the development of wisdom medical. How to protect the personal information of patients in the cloud environment has become an urgent problem to be solved. Medical image watermarking technology is an effective method to solve this problem. Combining the characteristics of Tent chaos and Henon chaos, this paper designed a Tent-Henon-Map double chaos watermarking encryption method and designed a medical image encryption watermarking algorithm based on ridgelet-DCT transform. The watermark images were encrypted by the Tent-Henon-Map double chaos which had the characteristics of sensitive initial values and large key space. Then, the feature vectors of the medical images were extracted through ridgelet-DCT transform. On the basis of ordinary watermarking technology, combined with zero watermarking, third-party concepts, and cryptographic technology, watermarking had a good ability to resist image processing attacks. The experimental results showed that the key space of the algorithm was $${10}^{116}$$ 10 116 , which had better encryption and hard to crack. The time of watermark embedding and extraction were only 0.336 s and 0.439 s, with lower computational cost. And under high-strength conventional attacks and geometric attacks, the NC values of the algorithm were all greater than 0.55, which could effectively extract watermark information. It shown that the algorithm proposed had good robustness against conventional and geometric attacks It shown that the algorithm proposed had good robustness against conventional and geometric attacks, while taking into account the security.