Call for Paper - January 2024 Edition
IJCA solicits original research papers for the January 2024 Edition. Last date of manuscript submission is December 20, 2023. Read More

Role of Neural Network in Healthcare System

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Kiran Bala Dubey, Gyanesh Shrivastava

Kiran Bala Dubey and Gyanesh Shrivastava. Role of Neural Network in Healthcare System. International Journal of Computer Applications 183(10):37-40, June 2021. BibTeX

	author = {Kiran Bala Dubey and Gyanesh Shrivastava},
	title = {Role of Neural Network in Healthcare System},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2021},
	volume = {183},
	number = {10},
	month = {Jun},
	year = {2021},
	issn = {0975-8887},
	pages = {37-40},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2021921406},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Healthcare is the acquisition area in our today's necessity. Healthcare costs approximately the world is on the outgrowth, creating a strong necessity for new ways of supporting the need of the healthcare system. Neural networks have been evidently found in many promising applications of the healthcare domain. Neural Network is utilized as a knowledge discovery proficiency to identify the service quality factors that are important to patients.

Neural networks have parallel computing devices, which are fundamentally an activity to form a computer framework of the human brain. The primary objective of neural network is to create a system to do a variety of computational tasks quicker than the traditional systems. A neural network is utilized to learn pattern and relationship in data.

The purpose of this paper is to provide an exposure of the application of neural network systems in healthcare system. The Neural Network is a network of artificial neurons, same as found in human brains, for resolving artificial intelligence problems like pattern recognition, image identification, data compression, classification and optimization.


  1. Marcin Mrugalski, M. W., 2008. Confidence estimation of the multi-layer perceptron and its application in fault detection systems. ELSEVIER , pp. 895–906.
  2. J.P. Drouhard, R. S., 1996. A Neural Network Approach to Off-Line Signature Verification using Directional PDF. ESLEVIER , pp. 415-424.
  3. Felix Weninger, H. E., 2015. Speech Enhancement with LSTM Recurrent Neural Networks and its Application to Noise-Robust ASR. Springer International Publishing ,pp. 91-95.
  4. Patricia Melin, O. M., 2011. Face Recognition With an Improved Interval Type-2 Fuzzy Logic Sugeno Integral and Modular Neural Networks. IEEE , pp. 1001-1012.
  5. Lee, T.-L., 2004. Back-propagation neural network for long-term tidal predictions. ELSEVIER, pp. 225–238.
  6. 6.
  7. Filippo Amato, A. L.-M., 2013. Artificial neural networks in medical diagnosis. Journal of Applied Biomedicine , pp. 47-58.
  8. Verma, M., 2014. Medical Diagnosis using Back Propagation Algorithm in ANN . International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 1 , pp. 94-99.
  9. Pattichis, C. S., 2001. Adaptive Neural Network Imaging in Medical Systems . IEEE , pp. 313-317.


Neural Network, knowledge discovery, artificial intelligence