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JournalISSN: 0148-5598

Journal of Medical Systems 

Springer Science+Business Media
About: Journal of Medical Systems is an academic journal published by Springer Science+Business Media. The journal publishes majorly in the area(s): Health informatics & Health care. It has an ISSN identifier of 0148-5598. Over the lifetime, 3981 publications have been published receiving 104331 citations.


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Journal ArticleDOI
TL;DR: An App (called Healthcare Data Gateway (HGD) architecture based on blockchain is proposed to enable patient to own, control and share their own data easily and securely without violating privacy, which provides a new potential way to improve the intelligence of healthcare systems while keeping patient data private.
Abstract: Healthcare data are a valuable source of healthcare intelligence. Sharing of healthcare data is one essential step to make healthcare system smarter and improve the quality of healthcare service. Healthcare data, one personal asset of patient, should be owned and controlled by patient, instead of being scattered in different healthcare systems, which prevents data sharing and puts patient privacy at risks. Blockchain is demonstrated in the financial field that trusted, auditable computing is possible using a decentralized network of peers accompanied by a public ledger. In this paper, we proposed an App (called Healthcare Data Gateway (HGD)) architecture based on blockchain to enable patient to own, control and share their own data easily and securely without violating privacy, which provides a new potential way to improve the intelligence of healthcare systems while keeping patient data private. Our proposed purpose-centric access model ensures patient own and control their healthcare data; simple unified Indicator-Centric Schema (ICS) makes it possible to organize all kinds of personal healthcare data practically and easily. We also point out that MPC (Secure Multi-Party Computing) is one promising solution to enable untrusted third-party to conduct computation over patient data without violating privacy.

884 citations

Journal ArticleDOI
TL;DR: The fundamental mechanisms of WBAN including architecture and topology, wireless implant communication, low-power Medium Access Control (MAC) and routing protocols are reviewed and many useful solutions are discussed for each layer.
Abstract: Recent advances in microelectronics and integrated circuits, system-on-chip design, wireless communication and intelligent low-power sensors have allowed the realization of a Wireless Body Area Network (WBAN). A WBAN is a collection of low-power, miniaturized, invasive/non-invasive lightweight wireless sensor nodes that monitor the human body functions and the surrounding environment. In addition, it supports a number of innovative and interesting applications such as ubiquitous healthcare, entertainment, interactive gaming, and military applications. In this paper, the fundamental mechanisms of WBAN including architecture and topology, wireless implant communication, low-power Medium Access Control (MAC) and routing protocols are reviewed. A comprehensive study of the proposed technologies for WBAN at Physical (PHY), MAC, and Network layers is presented and many useful solutions are discussed for each layer. Finally, numerous WBAN applications are highlighted.

788 citations

Journal ArticleDOI
TL;DR: This work created a system where sensors communicate with a smart device that calls smart contracts and writes records of all events on the blockchain, which would support real-time patient monitoring and medical interventions and automate the delivery of notifications to all involved parties in a HIPAA compliant manner.
Abstract: As Internet of Things (IoT) devices and other remote patient monitoring systems increase in popularity, security concerns about the transfer and logging of data transactions arise. In order to handle the protected health information (PHI) generated by these devices, we propose utilizing blockchain-based smart contracts to facilitate secure analysis and management of medical sensors. Using a private blockchain based on the Ethereum protocol, we created a system where the sensors communicate with a smart device that calls smart contracts and writes records of all events on the blockchain. This smart contract system would support real-time patient monitoring and medical interventions by sending notifications to patients and medical professionals, while also maintaining a secure record of who has initiated these activities. This would resolve many security vulnerabilities associated with remote patient monitoring and automate the delivery of notifications to all involved parties in a HIPAA compliant manner.

620 citations

Journal ArticleDOI
TL;DR: A new field known as wireless body area networks (WBAN or simply BAN) has emerged to address the growing use of sensor technology in healthcare applications and security and privacy concerns are discussed.
Abstract: The use of wireless sensor networks (WSN) in healthcare applications is growing in a fast pace. Numerous applications such as heart rate monitor, blood pressure monitor and endoscopic capsule are already in use. To address the growing use of sensor technology in this area, a new field known as wireless body area networks (WBAN or simply BAN) has emerged. As most devices and their applications are wireless in nature, security and privacy concerns are among major areas of concern. Due to direct involvement of humans also increases the sensitivity. Whether the data gathered from patients or individuals are obtained with the consent of the person or without it due to the need by the system, misuse or privacy concerns may restrict people from taking advantage of the full benefits from the system. People may not see these devices safe for daily use. There may also possibility of serious social unrest due to the fear that such devices may be used for monitoring and tracking individuals by government agencies or other private organizations. In this paper we discuss these issues and analyze in detail the problems and their possible measures.

575 citations

Journal ArticleDOI
TL;DR: A comprehensive review of the current state-of-the-art in medical image analysis using deep convolutional networks is presented in this paper, where the challenges and potential of these techniques are also highlighted.
Abstract: The science of solving clinical problems by analyzing images generated in clinical practice is known as medical image analysis. The aim is to extract information in an affective and efficient manner for improved clinical diagnosis. The recent advances in the field of biomedical engineering have made medical image analysis one of the top research and development area. One of the reasons for this advancement is the application of machine learning techniques for the analysis of medical images. Deep learning is successfully used as a tool for machine learning, where a neural network is capable of automatically learning features. This is in contrast to those methods where traditionally hand crafted features are used. The selection and calculation of these features is a challenging task. Among deep learning techniques, deep convolutional networks are actively used for the purpose of medical image analysis. This includes application areas such as segmentation, abnormality detection, disease classification, computer aided diagnosis and retrieval. In this study, a comprehensive review of the current state-of-the-art in medical image analysis using deep convolutional networks is presented. The challenges and potential of these techniques are also highlighted.

570 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202371
2022109
2021110
2020209
2019332
2018262