Real-Time Remote Patient Monitoring: A Review of Biosensors Integrated with Multi-Hop IoT Systems via Cloud Connectivity

R Uddin, I Koo - Applied Sciences, 2024 - mdpi.com
This comprehensive review paper explores the intricate integration of biosensors with multi-
hop Internet of Things (IoT) systems, representing a paradigm shift in healthcare through …

Computational Frontiers in Aptamer-Based Nanomedicine for Precision Therapeutics: A Comprehensive Review

S Kumar, A Mohan, NR Sharma, A Kumar… - ACS …, 2024 - ACS Publications
In the rapidly evolving landscape of nanomedicine, aptamers have emerged as powerful
molecular tools, demonstrating immense potential in targeted therapeutics, diagnostics, and …

Intelligent Millimeter-Wave System for Human Activity Monitoring for Telemedicine

AK Alhazmi, MA Alanazi, AH Alshehry, SM Alshahry… - Sensors, 2024 - mdpi.com
Telemedicine has the potential to improve access and delivery of healthcare to diverse and
aging populations. Recent advances in technology allow for remote monitoring of …

Leveraging reinforcement learning for advanced financial planning for effective personalization in economic forecasting and savings strategies

R Avacharmal, A Balakrishnan… - 2024 15th …, 2024 - ieeexplore.ieee.org
There is rarely a single response that can be considered “right” when it comes to the domain
of financial guidance and planning. Traditional algorithms have been successful in …

A Novel Prognostic Model Using Chaotic CNN with Hybridized Spoofing for Enhancing Diagnostic Accuracy in Epileptic Seizure Prediction

P Palanisamy, S Urooj, R Arunachalam… - Diagnostics, 2023 - mdpi.com
Epileptic seizure detection has undergone progressive advancements since its conception
in the 1970s. From proof-of-concept experiments in the latter part of that decade, it has now …

Mitigating Annotation Burden in Active Learning with Transfer Learning and Iterative Acquisition Functions

R Avacharmal, S Pamulaparthyvenkata… - 2024 15th …, 2024 - ieeexplore.ieee.org
In situations where there is a lack of readily available annotated data, active learning is a
useful tactic. To increase the model's generalization, it entails training a model on a …

Comprehensive investigation on Deep learning models: Applications, Advantages, and Challenges

R Avacharmal, S Pamulaparthyvenkata… - 2024 15th …, 2024 - ieeexplore.ieee.org
Artificial intelligence (AI) and machine learning (ML) have been completely transformed by
deep learning (DL), which provides unmatched power in handling massive, unstructured …

Validating wound severity assessment via region-anchored convolutional neural network model for mobile image-based size and tissue classification

Y Jaganathan, S Sanober, SMA Aldossary, H Aldosari - Diagnostics, 2023 - mdpi.com
Evaluating and tracking the size of a wound is a crucial step in wound assessment. The
measurement of various indicators on wounds over time plays a vital role in treating and …

[HTML][HTML] Artificial Intelligence for Remote Patient Monitoring: Advancements, Applications, and Challenges

M Farrokhi, F Taheri, A Moeini, M Farrokhi, MZS Alireza… - Kindle, 2024 - preferpub.org
Artificial Intelligence (AI) has emerged as a transformative force in the healthcare sector,
particularly in the realm of remote patient monitoring (RPM). RPM involves the collection …

Smart Malaria Classification: A Novel Machine Learning Algorithms for Early Malaria Monitoring and Detecting Using IoT-Based Healthcare Environment

AM Ayalew, WS Admass, BM Abuhayi, GS Negashe… - Sensing and …, 2024 - Springer
Malaria, caused by the Plasmodium parasite and transmitted by female Anopheles
mosquitoes, poses a significant risk to nearly half of the global population, with sub-Saharan …