The Imperative Role of Pervasive Data in Healthcare

Sathio, Anwar Ali; Brohi, Arz Muhammad

doi:10.1007/978-3-030-77746-3_2

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…A proposed blockchain framework for a facemask detection CNN model-oriented system can provide enhanced security, privacy, and accountability for the system [27,29,30] . The blockchain can store and manage the data generated [36,40]by the CNN model, such as the results of facemask detection and any associated metadata [25,42,47,55].…”

Section: Blockchain Framework Design and Cnn Integrationmentioning

confidence: 99%

A Blockchain-Enabled Machine Learning Mask Detection method for Prevention of Pandemic Diseases

Sathio,

Awan,

Panhwar

et al. 2023

VAWKUM trans. comput. sci.

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During the COVID-19 pandemic, finding effective methods to prevent the spread of infectious diseases has become critical. One important measure for reducing the transmission of airborne viruses is wearing face masks but enforcing mask-wearing regulations can be difficult in many settings. Real-time and accurate monitoring of mask usage is needed to address this challenge. To do so, we propose a method for mask detection using a convolutional neural network (CNN) and blockchain technology. Our system involves training a CNN model on a dataset of images of people with and without masks and then deploying it on IoT-enabled devices for real-time monitoring. The use of blockchain technology ensures the security and privacy of the data and enables the efficient sharing of resources among network participants. Our proposed system achieved 99% accuracy through CNN training and was transformed into a blockchain-enabled network mechanism with QR validation of every node for authentication. This approach has the potential to be an effective tool for promoting compliance with mask-wearing regulations and reducing the risk of infection. We present a framework for implementing this technique and discuss its potential benefits and challenges

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Section: Blockchain Framework Design and Cnn Integrationmentioning

confidence: 99%

A Blockchain-Enabled Machine Learning Mask Detection method for Prevention of Pandemic Diseases

Sathio,

Awan,

Panhwar

et al. 2023

VAWKUM trans. comput. sci.

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“…Linguistic features are useful to select keyphrases that have higher relevancy to content of webpage. This paper improves the performance of method D-rank [12,[15][16][17] by adding two additional things first adding linguistic features and change in other previous features. Second, including bigrams and noun phrases as candidate keywords.…”

Section: Introductionmentioning

confidence: 99%

W-rank: A keyphrase extraction method for webpage based on linguistics and DOM-base features

Shah,

Ahmed,

Sathio

et al. 2023

VAWKUM trans. comput. sci.

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This paper addresses the problem of an automatic keyphrase extraction for a webpage text. Our method is unsupervised, and we call it W-rank. In our method, first we extract the text of a webpage and tokenize into three different candidate words list: unigram ,bigrams and noun phrases. Then we assign score to all words based on their individual appearance in linguistic and DOM-based feature sets. In the final step, we rank these candidate words using score and select top 5 keyphrase from each list and combine them as a final keyphrases for a given webpage. We focus more on the relevancy of keyphrases to its content using linguistic features. We compare our method with other methods using precision, recall and f-score. The experimental result shows, W-rank improves the performance of our previous method D-rank and outperforms other state of art methods.

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The Pillars of Safety: Unveiling the Impact of Medication Usage on Public and Patient Wellbeing

Khan,

CV,

Rekha

2024

JCPP

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Background: The comprehensive management of various health conditions within the community is heavily reliant on the crucial role of medications. Objective: The primary objective of this research is to investigate medication usage patterns, adherence, and associated factors among a diverse participant pool. The study aims to assess the prevalence of prescription medication use, consumption patterns, adherence rates, and the methods employed by participants for managing their medicines. Furthermore, the study explores participants' experiences with side effects and evaluates their satisfaction with prescribed treatments. Methods: A prospective cross-sectional design was employed for data collection, utilizing a self-administered Medication Usage Survey distributed through Google Forms. Participants were recruited through various channels, and data were collected anonymously. Results: A total of 103 participants contributed to the study, with a diverse demographic composition. The majority identified as female (60.19%), and participants spanned various age groups, reflecting a comprehensive representation. Geographically, the study included participants from multiple locations, with Bengaluru being the predominant location (80.58%). Participants reported diverse health conditions, with 69 individuals (66.99%) on prescription medications. Consumption patterns revealed that 57.3% took medications daily, while adherence varied, with 36.9% reporting missed doses. Side effects were reported by a small percentage (12.66%) of participants, and various methods were employed for managing medicines. Overall, treatment satisfaction varied among participants. Conclusion: This research provides valuable insights into medication usage patterns and associated factors among a diverse participant pool.

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The Imperative Role of Pervasive Data in Healthcare

Cited by 3 publications

References 26 publications

A Blockchain-Enabled Machine Learning Mask Detection method for Prevention of Pandemic Diseases

A Blockchain-Enabled Machine Learning Mask Detection method for Prevention of Pandemic Diseases

W-rank: A keyphrase extraction method for webpage based on linguistics and DOM-base features

The Pillars of Safety: Unveiling the Impact of Medication Usage on Public and Patient Wellbeing

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