Kidney Cancer Prediction Empowered with Blockchain Security Using Transfer Learning

Nasir, Muhammad Umar; Zubair, Muhammad; Ghazal, Taher M.; Khan, Muhammad Farhan; Ahmad, Munir; Rahman, Atta; Hamadi, Hussam Al; Khan, Muhammad Adnan; Mansoor, Wathiq

doi:10.3390/s22197483

Cited by 21 publications

(11 citation statements)

References 34 publications

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“…With the adoption of a blockchainbased hospital management system, the healthcare industry has taken a significant step toward providing high-quality care while ensuring patients' privacy and confidentiality. It is even essential while using internet of medical things (IoMT) devices [46][47][48][49][50].…”

Section: Resultsmentioning

confidence: 99%

Blockchain Empowered Interoperable Framework for Smart Healthcare

Rahman,

Almomen,

Albahrani

et al. 2024

MMEP

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In the past, healthcare industry used paper-based systems to manage and store medical records. However, these systems are vulnerable to data breaches, loss, and errors. To overcome these issues, a research study has been conducted to create a safe and efficient Electronic Data Interchange (EDI) system for healthcare using blockchain technology. The study utilized various tools and methods including Python as the programming language to implement the blockchain environment, the pyQT5 library for graphical user interface (GUI), and the MySQL database management system as a repository for Electronic Health Records (EHR) with DBeaver, a cross-platform tool for data management. The research work involves the development of a blockchain-based smart contract for the storage, exchange, and retrieval of EHR. Additionally, a Python application based on pyQT5 is created to provide users with a friendly GUI. The proposed blockchain-based healthcare system provides a secure and efficient platform for storing and managing EHR as well as enabling secure EDI among healthcare stakeholders like practices, doctors, labs, and pharmacies. Furthermore, the system is scalable and user-friendly, and includes various features like patient visits, history, practices, doctors, and appointment scheduling. Blockchain technology ensures EHR integrity, secure EDI, and confidentiality, while the user-friendly interface enhances the user experience compared to the existing EDI standards like health level 7 (HL7).

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Section: Resultsmentioning

confidence: 99%

Blockchain Empowered Interoperable Framework for Smart Healthcare

Rahman,

Almomen,

Albahrani

et al. 2024

MMEP

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“…To address these issues, future work can extend the findings of this study by including more radiographical measurements to cover more pelvis related diseases in conjunction with transfer learning [45]. Additionally, utilizing online deployed models to continuously feed the model with new data that are validated by the medical professionals of the system will improve the long-term performance of the automatic DDH diagnosis.…”

Section: Discussionmentioning

confidence: 96%

Assessing Acetabular Index Angle in Infants: A Deep Learning-Based Novel Approach

Jan,

Rahman,

Busaleh

et al. 2023

J. Imaging

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Developmental dysplasia of the hip (DDH) is a disorder characterized by abnormal hip development that frequently manifests in infancy and early childhood. Preventing DDH from occurring relies on a timely and accurate diagnosis, which requires careful assessment by medical specialists during early X-ray scans. However, this process can be challenging for medical personnel to achieve without proper training. To address this challenge, we propose a computational framework to detect DDH in pelvic X-ray imaging of infants that utilizes a pipelined deep learning-based technique consisting of two stages: instance segmentation and keypoint detection models to measure acetabular index angle and assess DDH affliction in the presented case. The main aim of this process is to provide an objective and unified approach to DDH diagnosis. The model achieved an average pixel error of 2.862 ± 2.392 and an error range of 2.402 ± 1.963° for the acetabular angle measurement relative to the ground truth annotation. Ultimately, the deep-learning model will be integrated into the fully developed mobile application to make it easily accessible for medical specialists to test and evaluate. This will reduce the burden on medical specialists while providing an accurate and explainable DDH diagnosis for infants, thereby increasing their chances of successful treatment and recovery.

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“…Al. Conducted a study where they introduced a model that combines the Internet of Medical Things (IoMT) transfer learning techniques and deep learning algorithms to identify early stage kidney cancer (Nasir et al, 2022). To ensure the security of patients data this model incorporates clouds based on technology and transfer learning trained models.…”

Section: Literature Reviewmentioning

confidence: 99%

Blockchain Security-Efficiency Analysis based on DEA-SBM Model

VO,

WANG,

YANG

et al. 2023

EPSTEM

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It is estimated that by 2023 the security market will reach a value of $1.4 billion. This growth is primarily driven by the increasing use of technology in sectors like finance, healthcare and logistics. As more companies adopt technology there is a growing need to protect their data from hacking and other malicious activities. The security of the network plays a role in ensuring the implementation and adoption of technology. Given the rise in cyberattacks and data breaches it is expected that the importance of security will continue to grow in the coming years. In this study we will explore some companies that specialize in providing security solutions. Our analysis will be based on three factors and two desired outcomes. The selected companies include Hacken, Quantstamp, OpenZeppelin, Trail of Bits, ConsenSys, Certik, LeastAuthority, PWC Switzerland, Slowmist and Runtime Verification. The purpose of this research paper is to assess the effectiveness of the security industry for decision makers, experts and government entities. By gaining insights into this sector and enhancing network security measures for implementations, across industries.

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Kidney Cancer Prediction Empowered with Blockchain Security Using Transfer Learning

Cited by 21 publications

References 34 publications

Blockchain Empowered Interoperable Framework for Smart Healthcare

Blockchain Empowered Interoperable Framework for Smart Healthcare

Assessing Acetabular Index Angle in Infants: A Deep Learning-Based Novel Approach

Blockchain Security-Efficiency Analysis based on DEA-SBM Model

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