International Journal of Electronic Healthcare (4 papers in press)

Regular Issues

• Development of a blockchain-based architecture for the health data management and sharing  
  by Madhumita Das, Durjoy Majumder 
  Abstract: Database is important in diseases management. Information technology helps in disease database management in different healthcare organisations through LAN-based servers. Hence, patients or anybody from the community do not have access to such databases. Most of the public databases provide cross-sectional information about a specific disease. For providing a quality healthcare to the individual patients, emphasis is put to clinical data analytics; however, it requires individual patients’ clinical datasets with time-varying data points. In fact, the aggregation of such individual patients’ data into a large database could be considered as the more robust evidence of big data analytics and evidence-based clinical decisions. Considering these, a community driven disease (CDD) database portal has been developed, blockchain technology is adopted to connect its four independent modules: user, corporate, visitors and admin. CDD is open to search but patients’ privacy is secured. It is patient-centric and stores individual patients’ data in a temporal manner.
  Keywords: disease database; dynamical data; digital health; fourth industrial revolution; telemedicine; community driven disease; CDD.
  DOI: 10.1504/IJEH.2024.10064693
   
  
• Trends, challenges and opportunities of artificial intelligence in healthcare  
  by Sumit Kumar, T.V. Vijay Kumar  
  Abstract: Over the past few decades, the global healthcare system has inducted several key technologies in order to provide improved health services in various medical fields. Although the expenditure in the healthcare sector has been rising exponentially, there is little or no significant improvement in the health outcomes. The present healthcare system generates a large amount of structured and unstructured data in the form of lab tests, blood pressure readings, medical images, genomic data, and other health related data generated by various physiologic monitoring devices. Processing and analysing such data would likely consume a lot of time and the resultant diagnosis could also be error prone. An alternate way to process and analyse such data is by using artificial intelligence, which recently has emerged as one of the most prominent technologies in the current era of the fourth industrial revolution. AI, unlike human physicians, can provide clinically more relevant results in specific healthcare tasks such as diagnosing various diseases, spotting tumours, and analysing high resolution healthcare images produced in domains like cardiology, dermatology, pathology, radiology, and ophthalmology. This paper focuses on recent advancements and applications of AI in healthcare, especially in medical image analysis. Also, the paper outlines the challenges faced by AI vis-á-vis healthcare and identifies the opportunities that it provides in the healthcare domain.
  Keywords: healthcare; electronic health records; medical images; artificial intelligence.
  DOI: 10.1504/IJEH.2024.10064890
   
  
• Internet of things enabled diabetic foot ulcer image analysis support for smart segmentation using virtual sensing  
  by Athi Vaishnavi Rengarajan, K. Mahalakshmi  
  Abstract: At present, the Internet of Things has developed tremendously. When researchers use this development in image processing according to modern science, they bring the best image manipulation methods to current research. Based on this, this research focuses on image segmentation analysis of diabetic foot ulcers in the presence of the Internet of Things. This research does intelligent segmentation analysis to detect diabetic foot ulcers better and treat them through virtual sensing. Regarding this, the proposed system forms the ‘multimodal compressed sensing segmentation ’ to enhance the segmentation quality. Through this, the smart internet of things for image segmentation analysis is established, using the smart internet of things with the risk analysis by smart risk analysis, and the group is made up of prominent clinical characteristics. This helps to make the validity and reliability assessment of diabetic foot ulcers by analysis of likelihood ratio, sensitivity, and specificity.
  Keywords: compressed sensing; diabetic foot ulcer; DFU; image segmentation; internet of things; IoT; range segmentation; smart segmentation; virtual sensing.
  DOI: 10.1504/IJEH.2024.10064891
   
  
• Adoption of Metaverse technologies in medical and nursing education  
  by Dimitrios Zarakovitis, Dimitrios Tsoromokos, Nikolaos Tsaloukidis, Athina Lazakidou 
  Abstract: Metaverse technology is a new challenging trend that is rapidly growing in the health sector. It combines the technology of both virtually (VR) and augmented reality (AR) and consists of artificial intelligent (AI) systems. It is used for simulating the physical educational programs of medical and nursing staff and offers the participants an immersive experience of a 3D world. The Metaverse environments play a vital role in training nurses and doctors in real working environments, such as prisons, holographic medical clinics and iconic cardiology centres, without the limitation of their physical presence. Furthermore, modern Metaverse applications enable users to learn human anatomy by wearing 3D headsets which allow them to navigate through the human body during a surgery or improve their cardiopulmonary resuscitation (CPR) techniques. Medical students can also use the Metaverse technology for educational reasons inside 3D chemistry laboratories where they can guide through 3D molecules and particles.
  Keywords: Metaverse; virtual reality; augmented reality; artificial intelligence; medical education; avatars; holographs; digital twins; NFT; patients.
  DOI: 10.1504/IJEH.2024.10065019