Journal of Artificial Intelligence and Copsule Networks最新文献

Role of Synthetic Data for Improved AI Accuracy 合成数据对提高人工智能准确性的作用

Journal of Artificial Intelligence and Copsule Networks Pub Date : 2023-09-01 DOI: 10.36548/jaicn.2023.3.008

None Ketha Dhana Veera Chaitanya, None Manas Kumar Yogi

引用次数: 0

Critical Studies on Lesion Segmentation in Medical Images 医学图像中病灶分割的关键研究

Journal of Artificial Intelligence and Copsule Networks Pub Date : 2023-09-01 DOI: 10.36548/jaicn.2023.3.005

Alok Kumar, None N. Mahendran

{"title":"Critical Studies on Lesion Segmentation in Medical Images","authors":"Alok Kumar, None N. Mahendran","doi":"10.36548/jaicn.2023.3.005","DOIUrl":"https://doi.org/10.36548/jaicn.2023.3.005","url":null,"abstract":"In medical images, lesion segmentation is used to locate and isolate abnormal structures. It is an essential part of medical image analysis for precise diagnosis and care. However, obstacles exist in medical image lesion segmentation owing to things like image noise, shape and size fluctuation, and poor image quality. Automated lesion segmentation methods include conventional image processing techniques, deep learning (DL) models and machine learning (ML) algorithms to name a few. Thresholding, region growth, and active contour models are examples of conventional methods, while decision trees, random forests, and support vector machines are examples of ML techniques. DL models particularly convolutional neural networks (CNNs), have shown extraordinary performance in lesion segmentation because to their innate potential to autonomously collect high-level characteristics. The objective of the research is to study lesion segmentation in medical images and explore different methods for accurate and precise diagnosis and care.The research focuses on the obstacles faced in lesion segmentation in medical images, such as image noise, shape and size fluctuation, and poor image quality. The research also highlights the need for evaluation metrics, such as sensitivity, specificity, Dice coefficient, and Hausdorff distance, to assess the performance of lesion segmentation algorithms. Additionally, the research emphasizes the importance of annotated datasets for training and evaluating the performance of segmentation algorithms.","PeriodicalId":500183,"journal":{"name":"Journal of Artificial Intelligence and Copsule Networks","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135433679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blockchain-based Electronic Health Record Management System 基于区块链的电子健康档案管理系统

Journal of Artificial Intelligence and Copsule Networks Pub Date : 2023-09-01 DOI: 10.36548/jaicn.2023.3.006

Sulav Shrestha, Sagar Panta

{"title":"Blockchain-based Electronic Health Record Management System","authors":"Sulav Shrestha, Sagar Panta","doi":"10.36548/jaicn.2023.3.006","DOIUrl":"https://doi.org/10.36548/jaicn.2023.3.006","url":null,"abstract":"The Blockchain-based Electronic Health Record (B-EHR) system represents a significant advancement in healthcare data management. Concerns over data confidentiality and security have become increasingly critical in the healthcare sector, given the need for immediate data accessibility. Traditional centralized systems face accessibility issues, necessitating a transformative solution, and blockchain technology emerges as a promising candidate. This research introduces a patient-controlled, blockchain-based system that efficiently manages and safeguards individuals' health-related data. By harnessing the Ethereum network and utilizing tools such as Ganache, Solidity, and web3.js, this system takes a systematic approach to overcome the limitations of centralized systems. Smart contracts, the basis of blockchain technology, serve as the backbone for storing and processing patients' data in a decentralized manner. Transactions are conducted securely through these smart contracts, ensuring patient privacy and data security. Notably, any modifications to transactions can be verified and propagated across the entire distributed network, enhancing data integrity. Complementing this system is a cryptocurrency wallet like MetaMask, providing a centrally controlled repository where records can be swiftly accessed and secured by authorized individuals, including doctors and patients. This integration significantly improves data accessibility and security within the healthcare domain. Ultimately, this research aims to leverage blockchain technology for simultaneous data retrieval, enhancing efficiency, credibility, and accessibility. It offers a robust framework for securely storing data with tailored access permissions and facilitates the safe transfer of patient medical records. In essence, it introduces a swift and secure health record system and an innovative protocol, promoting greater transparency and ownership of sensitive data in the healthcare sector through blockchain integration.","PeriodicalId":500183,"journal":{"name":"Journal of Artificial Intelligence and Copsule Networks","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135686484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sustainable Energy Transition: Analyzing the Impact of Renewable Energy Sources on Global Power Generation 可持续能源转型:分析可再生能源对全球发电的影响

Journal of Artificial Intelligence and Copsule Networks Pub Date : 2023-09-01 DOI: 10.36548/jaicn.2023.3.007

None Rahul Kumar Jha

引用次数: 0

Segmentation of Microscopy images using Multi-Scale Retinex with Chromacity Preservation and Otsu Thresholding 基于色度保存和Otsu阈值的多尺度视网膜显微图像分割

Journal of Artificial Intelligence and Copsule Networks Pub Date : 2023-03-20 DOI: 10.36548//jaicn.2023.1.002

Ajay Yadav, Abhijeet Singh, Adarsh Singh, Anupam Yadav, Sashank Singh

引用次数: 0