التفاصيل البيبلوغرافية
| العنوان: |
Privacy Considerations in Medical Technology: Role of Federated Learning and Differential Privacy in Wearable Devices. |
| المؤلفون: |
Waqar, Ayaan |
| المصدر: |
International Journal of High School Research; Apr2024, Vol. 6 Issue 4, p17-21, 5p |
| مصطلحات موضوعية: |
MEDICAL technology, WEARABLE technology, FEDERATED learning, MACHINE learning, INTERNET security |
| مستخلص: |
Artificial intelligence (AI), specifically machine learning, has a considerable impact on improving the speed and accuracy of diagnosis in healthcare, leading to better outcomes. However, the increased use of technology in healthcare has raised privacy concerns caused by a need for robust security protocols. We review literature published between 2019-2023 in advanced journals in the field of medical and computer sciences to understand the advances in AI and its increased use in wearable devices and their significant benefits. The paper delves deep into the privacy concerns arising from remote transferring of sensitive data, thus leading to a higher probability of data leakage and breach. We then identify Differential Privacy (DP) in Federated Machine Learning (FML) and its use as a potential solution for data privacy and security concerns. The reviewed literature highlights that in the healthcare domain, particularly regarding wearable sensors, DP enables enhanced privacy and is a promising approach for building trust between users, healthcare devices, and healthcare professionals. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
