AIMC Topic: Computer Security

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Assessing the Impact of Federated Learning and Differential Privacy on Multi-centre Polyp Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Federated Learning (FL) is emerging in the medical field to address the need for diverse datasets while complying with data protection regulations. This decentralised learning paradigm allows hospitals (clients) to train machine learning models local...

A review on legal issues of medical robots.

Medicine
This paper examines the legal challenges associated with medical robots, including their legal status, liability in cases of malpractice, and concerns over patient data privacy and security. And this paper scrutinizes China's nuanced response to thes...

Trustworthy Precision Medicine: An Interpretable Approach to Detecting Anomalous Behavior of IoT Devices.

Studies in health technology and informatics
The growing integration of Internet of Things (IoT) technology within the healthcare sector has revolutionized healthcare delivery, enabling advanced personalized care and precise treatments. However, this raises significant challenges, demanding rob...

Ethical considerations for artificial intelligence in dermatology: a scoping review.

The British journal of dermatology
The field of dermatology is experiencing the rapid deployment of artificial intelligence (AI), from mobile applications (apps) for skin cancer detection to large language models like ChatGPT that can answer generalist or specialist questions about sk...

BadCLM: Backdoor Attack in Clinical Language Models for Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The advent of clinical language models integrated into electronic health records (EHR) for clinical decision support has marked a significant advancement, leveraging the depth of clinical notes for improved decision-making. Despite their success, the...

Exposing Vulnerabilities in Clinical LLMs Through Data Poisoning Attacks: Case Study in Breast Cancer.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Training Large Language Models (LLMs) with billions of parameters on a dataset and publishing the model for public access is the current standard practice. Despite their transformative impact on natural language processing (NLP), public LLMs present ...

Ensuring the integrity assessment of IoT medical sensors using hesitant fuzzy sets.

Health informatics journal
The Internet of Medical Things (IoMT) is transforming healthcare systems, but concerns about device integrity and sensitive data are growing. The study aims to develop a framework for evaluating and prioritizing integrity schemes in healthcare for I...

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Farmacia hospitalaria : organo oficial de expresion cientifica de la Sociedad Espanola de Farmacia Hospitalaria

Deep-KEDI: Deep learning-based zigzag generative adversarial network for encryption and decryption of medical images.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Medical imaging techniques have improved to the point where security has become a basic requirement for all applications to ensure data security and data transmission over the internet. However, clinical images hold personal and sensitive...

IoT-based external attacks aware secure healthcare framework using blockchain and SB-RNN-NVS-FU techniques.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: In recent times, there has been widespread deployment of Internet of Things (IoT) applications, particularly in the healthcare sector, where computations involving user-specific data are carried out on cloud servers. However, the network ...