The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?

This book is a reprint of the Special Issue entitled "The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?". Artificial intelligence is extending into the world of both digital radiology and digital pathology, and involves many scholars in the areas of biomedicine, technology, and bioethics. There is a particular need for scholars to focus on both the innovations in this field and the problems hampering integration into a robust and effective process in stable health care models in the health domain. Many professionals involved in these fields of digital health were encouraged to contribute with their experiences. This book contains contributions from various experts across different fields. Aspects of the integration in the health domain have been faced. Particular space was dedicated to overviewing the challenges, opportunities, and problems in both radiology and pathology. Clinal deepens are available in cardiology, the hystopathology of breast cancer, and colonoscopy. Dedicated studies were based on surveys which investigated students and insiders, opinions, attitudes, and self-perception on the integration of artificial intelligence in this field

An mHealth Technology for Chronic Wound Management

Increasingly, mobile consumer electronic devices are able to make meaningful applications in healthcare, and this chapter discusses the development of a mHealth app called SmartWoundCare, designed to document and assess chronic wounds on smartphones and tablets. Pressure ulcers (bedsores) were selected as the application area for SmartWoundCare due to their pervasiveness in healthcare and their associated impacts on patients’ quality of life and mortality, and electronic documentation is considered as an important intervention in pressure ulcer prevention and treatment. The chapter reviews the design of SmartWoundCare on Android and iOS platforms. Its benefits over paper‐based charting include automatically generated wound histories in graph and text formats, alerts and notifications for user‐set conditions, wound image galleries, and positioning for telehealth consultation by transmitting wound data across sites. The mobile app was implemented in a user trial in a long‐term care facility in Winnipeg, Canada, and the user trial illuminated that a key benefit of SmartWoundCare was the ability to take wound photographs. This feature had benefits for patients as well as caregivers. Consequently, algorithms were developed to analyse wound images for size and colour to provide additional indicators of wound progression

Using Machine Learning to address Data Accuracy and Information Integrity in Digital Health Delivery

Today, much of healthcare delivery is digital. In particular, there exists a plethora of mHealth solutions being developed. This in turn necessitates the need for accurate data and information integrity if superior mHealth is to ensue. Lack of data accuracy and information integrity can cause serious harm to patients and limit the benefits of mHealth technology. The described exploratory case study serves to investigate data accuracy and information integrity in mHealth, with the aim of incorporating Machine Learning to detect sources of inaccurate data and deliver quality information

Smart and Pervasive Healthcare

Smart and pervasive healthcare aims at facilitating better healthcare access, provision, and delivery by overcoming spatial and temporal barriers. It represents a shift toward understanding what patients and clinicians really need when placed within a specific context, where traditional face-to-face encounters may not be possible or sufficient. As such, technological innovation is a necessary facilitating conduit. This book is a collection of chapters written by prominent researchers and academics worldwide that provide insights into the design and adoption of new platforms in smart and pervasive healthcare. With the COVID-19 pandemic necessitating changes to the traditional model of healthcare access and its delivery around the world, this book is a timely contribution

Improving Nurses Wound Care Knowledge Utilizing an App

Practice Problem: Nurses needed additional wound care support, but formal training was not in the budget at this time. Nurses needed a quick reference guide to help them assess, document, and treat wounds correctly until the hospital could provide adequate training. PICOT: The PICOT question that guided this project is; “When treating wound care patients within a hospital setting (P), how does the implementation of a wound software app. (I) as compared to pre-existing nursing knowledge (C) increase a nurse’s self-reported ability to accurately assess and treat wounds (O) during a 10-week period? (T)” Evidence: Based on a thorough and rigorous review of the synthesized recommendations currently available, a wound software app has the capability of helping the nurses in the hospital who self-identified as having limited wound knowledge. The strength of the body of evidence is extensive, as evidenced by the quality, quantity, and consistency of the studies. Intervention: The intervention used an educational software phone application (app) to assist nurses in referencing information pertaining to wounds. The nurses self-reported their confidence level via a baseline survey and then this data will be compared to a post survey that analyzed their confidence level after utilizing the wound software app. during a 10-week period pre and post-intervention. Outcome: All participants (100%) indicated that they (a) felt comfortable using a wound app on phones or tablets, (b) would like to learn and participate in a training on a wound phone or tablet app, and (c) were interested in using a wound phone or tablet app for wound assessment, documentation, and treatment options. The two-tailed Wilcoxon signed rank test showed significant results based on an alpha value of .05, V = 0.00, z = -2.23, p = .026. Conclusion: In an organization where staff nurses are having difficulty merely understanding the basics of wounds, being able to have a reference guide can prove to be beneficial. Hospital administrators may save on wound related cost

Hybrid clouds for data-Intensive, 5G-Enabled IoT applications: an overview, key issues and relevant architecture

Hybrid cloud multi-access edge computing (MEC) deployments have been proposed as efficient means to support Internet of Things (IoT) applications, relying on a plethora of nodes and data. In this paper, an overview on the area of hybrid clouds considering relevant research areas is given, providing technologies and mechanisms for the formation of such MEC deployments, as well as emphasizing several key issues that should be tackled by novel approaches, especially under the 5G paradigm. Furthermore, a decentralized hybrid cloud MEC architecture, resulting in a Platform-as-a-Service (PaaS) is proposed and its main building blocks and layers are thoroughly described. Aiming to offer a broad perspective on the business potential of such a platform, the stakeholder ecosystem is also analyzed. Finally, two use cases in the context of smart cities and mobile health are presented, aimed at showing how the proposed PaaS enables the development of respective IoT applications.Peer ReviewedPostprint (published version