Applying Neural Networks to Predict Ventilator Demand: A Study of Pakistan's Healthcare Sector

The distribution companies that deal with ventilators in Pakistan face challenges related to inventory control because of inadequate product shelf life, shortages, excess inventory, and unnecessary stock. This study, which focuses on Pakistani ventilator distribution companies, aims to offer a novel approach to sales estimation, avoid unnecessary stock expenditures, and stop clientele loss brought on by ventilator shortages. The results of this study will help determine key elements and standards that Pakistani distributors of ventilators might employ to boost sales. Most ventilator distribution businesses in Pakistan are independent wholesalers that purchase stock from their stores and distribute it to customers. To maximize ventilator distribution firms' sales for various products, this study examined distribution and sales data from 2019 to 2024 for many locations and dates. To create an accurate sales forecasting model for a ventilator distribution company, this research also aims to apply artificial neural networks (ANN) for effective sales prediction. An Artificial Neural Network (ANN) model was trained using a dataset from ventilator distribution businesses and the proposed model produced an accuracy of 90%, which is good for early prediction.

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Publication Details

Journal
VFAST Transactions on Software Engineering
Published
2024-09-30
DOI
https://doi.org/10.21015/vtse.v12i3.1915
Citations
4
Primary Topic
Sleep and Work-Related Fatigue
Type
article
Field-Weighted Citation Impact
2.03
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article

Applying Neural Networks to Predict Ventilator Demand: A Study of Pakistan's Healthcare Sector

Abdul Ahad Abro, Noureddine Zahid, Syed Muhammad Daniyal, Mohsin Mubeen Abbasi et al.
4 citations
VFAST Transactions on Software Engineering
Sleep and Work-Related Fatigue
2.03
article

Applying Neural Networks to Predict Ventilator Demand: A Study of Pakistan's Healthcare Sector

Abdul Ahad Abro, Noureddine Zahid, Syed Muhammad Daniyal, Mohsin Mubeen Abbasi, Dilbar Hussain, Usama Amjad
article en
4 citations

Abstract

The distribution companies that deal with ventilators in Pakistan face challenges related to inventory control because of inadequate product shelf life, shortages, excess inventory, and unnecessary stock. This study, which focuses on Pakistani ventilator distribution companies, aims to offer a novel approach to sales estimation, avoid unnecessary stock expenditures, and stop clientele loss brought on by ventilator shortages. The results of this study will help determine key elements and standards that Pakistani distributors of ventilators might employ to boost sales. Most ventilator distribution businesses in Pakistan are independent wholesalers that purchase stock from their stores and distribute it to customers. To maximize ventilator distribution firms' sales for various products, this study examined distribution and sales data from 2019 to 2024 for many locations and dates. To create an accurate sales forecasting model for a ventilator distribution company, this research also aims to apply artificial neural networks (ANN) for effective sales prediction. An Artificial Neural Network (ANN) model was trained using a dataset from ventilator distribution businesses and the proposed model produced an accuracy of 90%, which is good for early prediction.

VFAST Transactions on Software EngineeringVol. 12(3)
Iqra University (PK)
Openalex Percentile: Top 12%
Sleep and Work-Related Fatigue
2.03
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