Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.9K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.9K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

213
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
213

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

An Enhancement on Convolutional Artificial Intelligent Based Diagnosis for Skin Disease Using Nanotechnology Sensors.

Computational intelligence and neuroscience·2022
Same author

Implementation of Artificial Neural Network to Predict Diabetes with High-Quality Health System.

Computational intelligence and neuroscience·2022
Same author

Extraction of the molecular level biomedical event trigger based on gene ontology using radial belief neural network techniques.

Bio Systems·2020
See all related articles

Related Experiment Video

Updated: Sep 17, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

Advanced predictive disease modeling in biomedical IoT using the temporal adaptive neural evolutionary algorithm.

Chandragandhi S1, Arvind C2, Srihari K3

  • 1Department of Artificial Intelligence and Data Science, Karpagam Institute of Technology, Coimbatore, India. chandragandhi09@gmail.com.

Scientific Reports
|July 2, 2025
PubMed
Summary

A new Temporal Adaptive Neural Evolutionary Algorithm (TANEA) improves predictive disease modeling in biomedical IoT. This advanced approach enhances accuracy and efficiency for real-time health monitoring and early disease detection.

Keywords:
Biological sciencesBiomedical IoTEngineeringHealth scienceMachine learningPredictive disease modelingTemporal adaptive neural evolutionary algorithm (TANEA)Temporal data analysis

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

751
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K

Related Experiment Videos

Last Updated: Sep 17, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

751
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K

Area of Science:

  • Biomedical Engineering
  • Computer Science
  • Data Science

Background:

  • Biomedical Internet of Things (IoT) systems are vital for modern healthcare, relying on predictive modeling for disease diagnosis.
  • Existing models like LSTM and XGBoost struggle with the complexity and temporal dynamics of health data streams.
  • Early disease detection and intervention necessitate accurate and efficient predictive models within biomedical IoT.

Purpose of the Study:

  • To introduce the Temporal Adaptive Neural Evolutionary Algorithm (TANEA), a novel approach to enhance predictive modeling in biomedical IoT.
  • To address the limitations of current models in handling complex, temporal health data.
  • To improve the precision and reliability of disease prediction in IoT-based healthcare.

Main Methods:

  • Leveraging temporal data patterns inherent in biomedical sensor readings.
  • Implementing an adaptive mechanism to account for dynamic changes in data streams.
  • Utilizing an evolutionary approach for optimized feature selection within the predictive model.

Main Results:

  • TANEA demonstrated superior performance compared to traditional predictive modeling methods.
  • Achieved significant improvements in predictive accuracy and reduced computational overhead.
  • Showcased faster convergence rates and adaptability to diverse biomedical data patterns.

Conclusions:

  • TANEA offers a robust solution for intelligent health monitoring and proactive interventions in biomedical IoT.
  • The algorithm's adaptability enhances real-time decision-making in IoT-based healthcare environments.
  • TANEA has the potential to revolutionize predictive disease modeling and healthcare delivery.