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 …

Heart rate variability for medical decision support systems: A review

O Faust, W Hong, HW Loh, S Xu, RS Tan… - Computers in biology …, 2022 - Elsevier
Abstract Heart Rate Variability (HRV) is a good predictor of human health because the heart
rhythm is modulated by a wide range of physiological processes. This statement embodies …

Wearable devices for remote monitoring of heart rate and heart rate variability—what we know and what is coming

N Alugubelli, H Abuissa, A Roka - Sensors, 2022 - mdpi.com
Heart rate at rest and exercise may predict cardiovascular risk. Heart rate variability is a
measure of variation in time between each heartbeat, representing the balance between the …

Practical privacy-preserving Gaussian process regression via secret sharing

J Luo, Y Zhang, J Zhang, S Qin… - Uncertainty in …, 2023 - proceedings.mlr.press
Gaussian process regression (GPR) is a non-parametric model that has been used in many
real-world applications that involve sensitive personal data (eg, healthcare, finance, etc.) …

Understanding the pivotal role of the vagus nerve in Health from pandemics

CM Rangon, A Niezgoda - Bioengineering, 2022 - mdpi.com
The COVID-19 pandemic seems endless with the regular emergence of new variants. Is the
SARS-CoV-2 virus particularly evasive to the immune system, or is it merely disrupting …

Three‐Dimensional Poincaré Plot Analysis for Heart Rate Variability

B Wang, D Liu, X Gao, Y Luo - Complexity, 2022 - Wiley Online Library
For the limitation of Poincaré plot analysis, the three‐dimensional Poincaré plot analysis is
proposed to analyze the heart rate variability. Firstly, the Poincaré plot and some classic …

Machine learning, a new tool for the detection of immunodeficiency patterns in systemic lupus erythematosus

I Usategui, J Barbado, AM Torres… - Journal of …, 2023 - journals.sagepub.com
Systemic lupus erythematosus (SLE) is a complex autoimmune disease that affects several
organs and causes variable clinical symptoms. Early diagnosis is currently the most effective …

KPCA-WRF-prediction of heart rate using deep feature fusion and machine learning classification with tuned weighted hyper-parameter

GJ Christabel, AC Subhajini - Network: Computation in Neural …, 2023 - Taylor & Francis
The rapid advancement of technology such as stream processing technologies, deep-
learning approaches, and artificial intelligence plays a prominent and vital role, to detect …

Efficient privacy-preserving Gaussian process via secure multi-party computation

S Liu, J Luo, Y Zhang, H Wang, Y Yu, Z Xu - Journal of Systems …, 2024 - Elsevier
Gaussian processes (GPs), known for their flexibility as non-parametric models, have been
widely used in practice involving sensitive data (eg, healthcare, finance) from multiple …

Tunable Q-factor wavelet transform based identification of diabetic patients using ECG signals

A Jain, A Verma, AK Verma, V Bajaj - Computer Methods in …, 2024 - Taylor & Francis
Diabetes is a chronic health condition that is characterized by increased levels of glucose
(sugar) in the blood. It can have harmful effects on different parts of the body, such as the …