Enhancing Healthcare Access in Remote Areas Using Neural Network Algorithms, Overcoming Distance and Infrastructure Barriers.

EasyChair Preprint 13276

Abstract

Access to healthcare services in remote areas is a persistent challenge due to distance and infrastructure barriers. However, advancements in technology, particularly the use of neural network algorithms, have the potential to overcome these barriers and enhance healthcare access. This abstract provides an overview of how neural network algorithms can improve healthcare access in remote areas.

With their ability to analyze complex data patterns and make predictions, neural network algorithms can play a crucial role in remote healthcare. Telemedicine, enabled by neural network algorithms, allows healthcare professionals to diagnose patients and provide consultations remotely. Algorithms can analyze medical images, enabling accurate diagnoses and early detection of diseases. Data privacy and security are critical considerations in telemedicine implementation.

Furthermore, wearable devices equipped with neural network algorithms enable remote monitoring of vital signs. Real-time analysis of data from wearables can detect abnormalities and alert healthcare professionals, ensuring timely interventions. Concerns related to data accuracy, reliability, and patient privacy must be addressed in the deployment of wearable devices.

Keyphrases: Deployment, Infrastructure barriers, Internet Connectivity, neural network algorithms, power supply, training

@booklet{EasyChair:13276,
  author    = {Edwin Frank and Harold Jonathan},
  title     = {Enhancing Healthcare Access in Remote Areas Using Neural Network Algorithms, Overcoming Distance and Infrastructure Barriers.},
  howpublished = {EasyChair Preprint 13276},
  year      = {EasyChair, 2024}}