Secure and Robust Machine Learning for Healthcare: A Survey
<p>Recent years have witnessed widespread adoption of machine learning (ML)/deep learning (DL) techniques due to their superior performance for a variety of healthcare applications ranging from the prediction of cardiac arrest from one-dimensional heart signals to computer-aided diagnosis (CAD...
محفوظ في:
| المؤلف الرئيسي: | Adnan Qayyum (16875936) (author) |
|---|---|
| مؤلفون آخرون: | Junaid Qadir (16494902) (author), Muhammad Bilal (737265) (author), Ala Al-Fuqaha (4434340) (author) |
| منشور في: |
2020
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Securing Machine Learning in the Cloud: A Systematic Review of Cloud Machine Learning Security
حسب: Adnan Qayyum (16875936)
منشور في: (2020) -
Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study
حسب: Muhammad Atif Butt (10849980)
منشور في: (2023) -
Explainable, trustworthy, and ethical machine learning for healthcare: A survey
حسب: Khansa Rasheed (17380573)
منشور في: (2022) -
Collaborative Federated Learning for Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge
حسب: Adnan Qayyum (16875936)
منشور في: (2022) -
Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey
حسب: Faria Nawshin (21841598)
منشور في: (2024)