MYeHealthAppCY: A Healthcare Mobile Application in Cyprus.

This paper presents MYeHealthAppCY, an mHealth solution designed to provide patients and healthcare providers in Cyprus with access to medical data. The application includes features such as an at-a-glance view of patient summary, comprehensive prescription management, teleconsultation, and the ability to store and access European Digital COVID Certificates (EUDCC). The application is an integral part of the eHealth4U platform targeting to implement a prototype EHR platform for national use. The application developed is based on FHIR and follows a strict adherence to widely used coding standards. The application was evaluated receiving satisfactory scores; however, significant work is still needed to deploy the application in production.

eHealth4U: A DEMO of a Prototype National Electronic Health Record for Cyprus.

In this paper we present a demonstration of a prototype national Electronic Health Record platform for Cyprus. This prototype is developed using the HL7 FHIR interoperability standard in combination with terminologies widely adopted by the clinical community such as the SNOMED CT and the LOINC. The system is organized in such a way to be user-friendly for its users, being the doctors and the citizens. The health-related data of this EHR are separated into three main sections, being the "Medical History", the "Clinical Examination" and the "Laboratory results". Business requirements include the Patient Summary as defined by the guidelines of the eHealth network and the International Patient Summary which are used as the base for all the sections of our EHR, together with additional medical information and functionality such as the organization of medical teams or the history of medical visits and episodes of care. From the doctor's point of view, one can search for patients who have granted the doctor with a consent and read or add/edit their EHR data by initiating a new visit as defined in the Cyprus National Law for eHealth. At the same time, doctors can organize their medical teams by managing the locations of each team and the members that belong to each team.

Computer-Aided Diagnosis by Tissue Image Analysis as an Optical Biopsy in Hysteroscopy.

This review of our experience in computer-assisted tissue image analysis (CATIA) research shows that significant information can be extracted and used to diagnose and distinguish normal from abnormal endometrium. CATIA enabled the evaluation and differentiation between the benign and malignant endometrium during diagnostic hysteroscopy. The efficacy of texture analysis in the endometrium image during hysteroscopy was examined in 40 women, where 209 normal and 209 abnormal regions of interest (ROIs) were extracted. There was a significant difference between normal and abnormal endometrium for the statistical features (SF) features mean, variance, median, energy and entropy; for the spatial grey-level difference matrix (SGLDM) features contrast, correlation, variance, homogeneity and entropy; and for the gray-level difference statistics (GLDS) features homogeneity, contrast, energy, entropy and mean. We further evaluated 52 hysteroscopic images of 258 normal and 258 abnormal endometrium ROIs, and tissue diagnosis was verified by histopathology after biopsy. The YCrCb color system with SF, SGLDM and GLDS color texture features based on support vector machine (SVM) modeling correctly classified 81% of the cases with a sensitivity and a specificity of 78% and 81%, respectively, for normal and hyperplastic endometrium. New technical and computational advances may improve optical biopsy accuracy and assist in the precision of lesion excision during hysteroscopy. The exchange of knowledge, collaboration, identification of tasks and CATIA method selection strategy will further improve computer-aided diagnosis implementation in the daily practice of hysteroscopy.

A Prototype of the National EHR system for Cyprus.

The aim of this paper is to present Cyprus' initiative for the design and the implementation of the prototype of the integrated electronic health record at a national level that will establish the foundations of the country's broader eHealth ecosystem. The latter, requires an interdisciplinary approach and scientific collaboration among various fields, including medicine, information and communication technologies, management, and finance, among others. The objective, is to design the system architecture, specify the requirements in terms of clinical content as well as the hardware infrastructure, but also implement European and national legislation with respect to privacy and security that govern sensitive medical data manipulation. The present study summarizes the outcomes of the 1st phase of this initiative, which comprises of the healthcare as well as the administrative requirements, user stories, data-flows and associated functionality. Moreover, leveraging the HL7 Fast Healthcare Interoperability Resources (FHIR) standard we highlight the concluded interoperability framework that allows genuine cross-system communication and defines third-party systems connectivity.Clinical Relevance- This work is strongly correlated with medicine since it describes the system requirements and the architecture of a national integrated electronic health records system.

Is Computer-Assisted Tissue Image Analysis the Future in Minimally Invasive Surgery? A Review on the Current Status of Its Applications.

PURPOSE: Computer-assisted tissue image analysis (CATIA) enables an optical biopsy of human tissue during minimally invasive surgery and endoscopy. Thus far, it has been implemented in gastrointestinal, endometrial, and dermatologic examinations that use computational analysis and image texture feature systems. We review and evaluate the impact of in vivo optical biopsies performed by tissue image analysis on the surgeon's diagnostic ability and sampling precision and investigate how operation complications could be minimized. METHODS: We performed a literature search in PubMed, IEEE, Xplore, Elsevier, and Google Scholar, which yielded 28 relevant articles. Our literature review summarizes the available data on CATIA of human tissues and explores the possibilities of computer-assisted early disease diagnoses, including cancer. RESULTS: Hysteroscopic image texture analysis of the endometrium successfully distinguished benign from malignant conditions up to 91% of the time. In dermatologic studies, the accuracy of distinguishing nevi melanoma from benign disease fluctuated from 73% to 81%. Skin biopsies of basal cell carcinoma and melanoma exhibited an accuracy of 92.4%, sensitivity of 99.1%, and specificity of 93.3% and distinguished nonmelanoma and normal lesions from benign precancerous lesions with 91.9% and 82.8% accuracy, respectively. Gastrointestinal and endometrial examinations are still at the experimental phase. CONCLUSIONS: CATIA is a promising application for distinguishing normal from abnormal tissues during endoscopic procedures and minimally invasive surgeries. However, the efficacy of computer-assisted diagnostics in distinguishing benign from malignant states is still not well documented. Prospective and randomized studies are needed before CATIA is implemented in clinical practice.

The role of tele-ophthalmology in diabetic retinopathy screening / Rol de la tele-oftalmología en el cribado de la retinopatía diabética

Diabetic retinopathy (DR) is the leading cause of legal blindness in the United States. Considering the increasing incidence of DR, it is extremely important to detect the most cost-effective tools for DR screening, so as to manage this surge in demand and the socioeconomic burden it places on the health care system. Despite the advances in retinal imaging, analysis techniques are still superseded by expert ophthalmologist interpretation. Teleophthalmology presents an immense opportunity, with high rates of sensitivity and specificity, to manage the steadily increasing demand for eye care of patients with diabetes, but challenges remain in the delivery of practical, viable, and clinically proven solutions

La retinopatía diabética (RD) es la causa principal de ceguera legal en los Estados Unidos. Teniendo en cuenta la creciente incidencia de RD, es extremadamente importante detectar las herramientas más económicas para su cribado, para poder gestionar esta demanda creciente, así como la carga socioeconómica que supone para el sistema sanitario. A pesar de los avances en términos de imagen retiniana, las técnicas de análisis siguen siendo reemplazadas por la interpretación de los oftalmólogos expertos. La tele-oftalmología se presenta como una gran oportunidad, con altas tasas de sensibilidad y especificidad, para gestionar el aumento constante de la atención ocular en los pacientes diabéticos, aunque la aportación de soluciones clínicamente probadas sigue suponiendo un reto

The role of tele-ophthalmology in diabetic retinopathy screening.

Diabetic retinopathy (DR) is the leading cause of legal blindness in the United States. Considering the increasing incidence of DR, it is extremely important to detect the most cost-effective tools for DR screening, so as to manage this surge in demand and the socioeconomic burden it places on the health care system. Despite the advances in retinal imaging, analysis techniques are still superseded by expert ophthalmologist interpretation. Teleophthalmology presents an immense opportunity, with high rates of sensitivity and specificity, to manage the steadily increasing demand for eye care of patients with diabetes, but challenges remain in the delivery of practical, viable, and clinically proven solutions.

A Web services-based exergaming platform for senior citizens: the Long Lasting Memories project approach to e-health care.

This piece of research describes an innovative e-health service that supports the cognitive and physical training of senior citizens and promotes their active ageing. The approach is adopted by the Long Lasting Memories (LLM) project, elements of which are discussed herein in the light of the functionalities provided to the users and the therapists. The aim of this work is to describe those technical elements that demonstrate the unique and integrative character of the LLM service, which is based on a modular Web service architecture, rendering the system available in different settings like the homes of seniors. The underlying database as well as the remote user interface empower therapists to set personalized training schemes, to view the progress of training sessions, as well as, adding new games and exercises into the system, thereby increasing the services sustainability and marketability.

A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer.

BACKGROUND: In the development of tissue classification methods, classifiers rely on significant differences between texture features extracted from normal and abnormal regions. Yet, significant differences can arise due to variations in the image acquisition method. For endoscopic imaging of the endometrium, we propose a standardized image acquisition protocol to eliminate significant statistical differences due to variations in: (i) the distance from the tissue (panoramic vs close up), (ii) difference in viewing angles and (iii) color correction. METHODS: We investigate texture feature variability for a variety of targets encountered in clinical endoscopy. All images were captured at clinically optimum illumination and focus using 720 x 576 pixels and 24 bits color for: (i) a variety of testing targets from a color palette with a known color distribution, (ii) different viewing angles, (iv) two different distances from a calf endometrial and from a chicken cavity. Also, human images from the endometrium were captured and analysed. For texture feature analysis, three different sets were considered: (i) Statistical Features (SF), (ii) Spatial Gray Level Dependence Matrices (SGLDM), and (iii) Gray Level Difference Statistics (GLDS). All images were gamma corrected and the extracted texture feature values were compared against the texture feature values extracted from the uncorrected images. Statistical tests were applied to compare images from different viewing conditions so as to determine any significant differences. RESULTS: For the proposed acquisition procedure, results indicate that there is no significant difference in texture features between the panoramic and close up views and between angles. For a calibrated target image, gamma correction provided an acquired image that was a significantly better approximation to the original target image. In turn, this implies that the texture features extracted from the corrected images provided for better approximations to the original images. Within the proposed protocol, for human ROIs, we have found that there is a large number of texture features that showed significant differences between normal and abnormal endometrium. CONCLUSION: This study provides a standardized protocol for avoiding any significant texture feature differences that may arise due to variability in the acquisition procedure or the lack of color correction. After applying the protocol, we have found that significant differences in texture features will only be due to the fact that the features were extracted from different types of tissue (normal vs abnormal).