[HTML][HTML] A systematic review of data fusion techniques for optimized structural health monitoring

S Hassani, U Dackermann, M Mousavi, J Li - Information Fusion, 2024 - Elsevier
Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …

[HTML][HTML] A survey of multimodal information fusion for smart healthcare: Map** the journey from data to wisdom

T Shaik, X Tao, L Li, H **e, JD Velásquez - Information Fusion, 2024 - Elsevier
Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …

[HTML][HTML] A secure healthcare 5.0 system based on blockchain technology entangled with federated learning technique

A Rehman, S Abbas, MA Khan, TM Ghazal… - Computers in Biology …, 2022 - Elsevier
In recent years, the global Internet of Medical Things (IoMT) industry has evolved at a
tremendous speed. Security and privacy are key concerns on the IoMT, owing to the huge …

COVID-19 detection from CBC using machine learning techniques

A Akhtar, S Akhtar, B Bakhtawar… - International Journal …, 2021 - journals.gaftim.com
Covid-19 pandemic has seriously affected the mankind with colossal loss of life around the
world. There is a critical requirement for timely and reliable detection of Corona virus …

Treatment response prediction in hepatitis C patients using machine learning techniques

AA Kashif, B Bakhtawar, A Akhtar… - International Journal …, 2021 - journals.gaftim.com
The proper prognosis of treatment response is crucial in any medical therapy to reduce the
effects of the disease and of the medication as well. The mortality rate due to hepatitis c virus …

Intelligent model to predict early liver disease using machine learning technique

TM Ghazal, AU Rehman, M Saleem… - … for Technology and …, 2022 - ieeexplore.ieee.org
Liver Disease (LD) is the main cause of death worldwide, affecting a large number of
people. A variety of factors affect the liver, resulting in this disease. The diagnosis of this …

Machine learning and deep learning predictive models for type 2 diabetes: a systematic review

L Fregoso-Aparicio, J Noguez, L Montesinos… - Diabetology & metabolic …, 2021 - Springer
Diabetes Mellitus is a severe, chronic disease that occurs when blood glucose levels rise
above certain limits. Over the last years, machine and deep learning techniques have been …

Secure IoMT for disease prediction empowered with transfer learning in healthcare 5.0, the concept and case study

TA Khan, A Fatima, T Shahzad, K Alissa… - IEEE …, 2023 - ieeexplore.ieee.org
Identifying human diseases remains a difficult process, even in the age of advanced
information technology and the smart healthcare industry 5.0. In the smart healthcare …

Hybrid stacked ensemble combined with genetic algorithms for diabetes prediction

J Abdollahi, B Nouri-Moghaddam - Iran Journal of Computer Science, 2022 - Springer
Diabetes is currently one of the most common, dangerous, and costly diseases globally
caused by increased blood sugar or a decrease in insulin in the body. Diabetes can have …

[HTML][HTML] Interpretable machine learning for personalized medical recommendations: A LIME-based approach

Y Wu, L Zhang, UA Bhatti, M Huang - Diagnostics, 2023 - mdpi.com
Chronic diseases are increasingly major threats to older persons, seriously affecting their
physical health and well-being. Hospitals have accumulated a wealth of health-related data …