Illuminating Healthcare Management: A Comprehensive Review of IoT-Enabled Chronic Disease Monitoring

Talpur, Mir Sajjad Hussain; Abro, Abdul Ahad; Ebrahim, Mansoor; Kandhro, Irfan Ali; Manickam, Selvakumar; Laghari, Shams Ul Arfeen; Dandoush, Abdulhalim; Uddin, Mueen

doi:10.1109/access.2024.3382011

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Cited by 3 publications

References 134 publications

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Smart Healthcare: Machine Learning Enabled WBAN for Early Detection of Chronic Diseases

Kumaran,

Princy,

Agnes

2024

2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS)

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Smart Healthcare: Machine Learning Enabled WBAN for Early Detection of Chronic Diseases

Kumaran,

Princy,

Agnes

2024

2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS)

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Quaternion Generative Adversarial Networks for loT based Chronic Kidney Disease Detection using Greylag Goose Optimization Algorithm

Shaik,

Chaudhary,

Abbineni

et al. 2024

2024 4th International Conference on Sustainable Expert Systems (ICSES)

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

Abbasi,

Daniyal,

Abro

et al. 2024

VFAST trans. softw. eng.

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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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Illuminating Healthcare Management: A Comprehensive Review of IoT-Enabled Chronic Disease Monitoring

Cited by 3 publications

References 134 publications

Smart Healthcare: Machine Learning Enabled WBAN for Early Detection of Chronic Diseases

Smart Healthcare: Machine Learning Enabled WBAN for Early Detection of Chronic Diseases

Quaternion Generative Adversarial Networks for loT based Chronic Kidney Disease Detection using Greylag Goose Optimization Algorithm

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

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