Introduction Health chatbots are increasingly being utilized in healthcare to combat COVID-19. However, few studies have explored the perception and willingness of end-users toward COVID-19-related chatbots. Furthermore, no studies have been conducted in Saudi Arabia. Aim This paper explored 166 end-users' perceived utilities of health chatbots in Saudi Arabia, and how their characteristics affect their perceptions. Methods We conducted a quantitative descriptive study by implementing an online survey. The survey asked 20 questions on participants' demographics and their perception of health chatbots' usefulness. Results We found that users were more willing to use health chatbots to seek general information about COVID-19 (82.5%) over seeking information regarding COVID-19 medical treatments (72.3%). Furthermore, participants with undergraduate degrees tend to use them to learn how to prevent COVID-19's spread (P = 0.015), to self-track COVID-19 symptoms (P = 0.028), and to seek information about medication (P = 0.035) in comparison to those who had postgraduate degrees. Participants who frequently searched for health information on the internet were more likely to look for nearby medical services using health chatbots (P = 0.023). Lastly, participants who provided any sort of healthcare services information were more likely to self-assess COVID-19 symptoms by using health chatbots (P = 0.036). Conclusion Participant awareness and use of health chatbots were low; however, most had positive perceptions of these emerging technologies and displayed willingness to use them. Further research is needed to capture the real-world usability of these novel technologies by employing more rigid methodological designs (e.g, field trials).

Introduction:With With the proliferation of available ICT services, several sensors and health applications have become ubiquitous, while many applications have been developed to detect certain health conditions and early signs of disease. Currently, all these services operate independently, and the available data is heterogeneous with limited value gained from its exploitation. Aim:The Data Sources and Gateways component aims at providing an abstracted and unified API to support the data accumulation from various sources including healthcare organisations, biosensors, laboratories and mobile applications. Meanwhile it tackles connectivity and communication issues with such information sources.Methods:The CrowdHEALTH Data Sources and Gateways Service incorporates four main services: The Configuration Service, The DB Connection Handling Service, The File Parsing Service and The RESTful Client Service.Results:The initial version of the component design has built upon the requirements collected from the use case participants acting also as data providers.Conclusion:These four services presented in this paper guide the implementation of the first version of the Data Sources and Gateways component software prototype. The Data Sources and Gateways component remains to be evaluated within the context of the project and be enriched in order to meet additional end user needs.

Introduction:Iron deficiency anemia (IDA) and β-thalassemia trait (β-TT) are the most common types of microcytic hypochromic anemias. The similarity and the nature of anemia-related symptoms pose a foremost challenge for discriminating between IDA and β-TT. Currently, advances in technology have gave rise to computer-based decision-making systems. Therefore, advances in artificial intelligence have led to the emergence of intelligent systems and the development of tools that can assist physicians in the diagnosis and decision-making.Aim:The aim of the present study was to develop a neural network based model (Artificial Neural Network) for accurate and timely manner of differential diagnosis of IDA and β-TT in comparison with traditional methods.Methods:In this study, an artificial neural network (ANN) model as the first precise intelligent method was developed for differential diagnosis of IDA and β-TT. Data set was retrieved from Complete Blood Count (CBC) test factors of 268 individuals referred to Padad private clinical laboratory at Ahvaz, Iran in 2018. ANN models with different topologies were developed and CBC indices were examined for diagnosis of IDA and β-TT. The proposed model was simulated using MATLAB software package version 2018. The results showed the best network architecture based on the advanced multilayer algorithm (4 input factors, 70 neurons with acceptable sensitivity, specificity, and accuracy). Finally, the results obtained from ANN diagnostic model was compared to existing discriminating indexes.Result:The results of this model showed that the specificity, sensitivity, and accuracy of the proposed diagnostic system were 92.33%, 93.13%, and 92.5%, respectably; i.e. the model could diagnose frequent occurrence of IDA in patients with β-TT.Conclusion:The results and evaluation of the developed model showed that the proposed neural network model has a proper accuracy and generalizability based on the initial factors of CBC testing compared to existing methods. This model can replace the high-cost methods and discriminating indices to distinguish IDA from β-TT and assist in accurate and timely manner diagnosis.

Introduction:The 12-lead ECG at admission of patients suffering from acute myocardial infarction (AMI) is mandatory for accurate diagnosis and prompt therapeutic measures, mainly reperfusion. It has been shown that recording additional ECG leads may improve the diagnostic accuracy and therefore, the prognosis of selected cases.Aim:The aim of the study was to assess the usefulness of the 15-lead ECG (12 classic plus 3 posterior leads) in the management of chest pain patients, especially when 12-lead ECG is not diagnostic of AMI.Methods:Total amount of 186 consecutive patients (127 men, 59 women, mean age 69.7±13.8 years) were admitted with an acute coronary syndrome. The initial ECG recorded the 12 classic leads, and subsequently, the 3 additional posterior leads. Demographic and clinical data, including ECG alterations and selected treatment strategy, were also studied. The cumulative impact of the 15-lead ECG on the diagnosis and management of AMI were, overall, evaluated.Results:The 12-lead ECG was diagnostic of ST-elevation AMI (STEMI) in 158 patients (Group A–84.5%) who were promptly reperfused. On the other hand, the interpretation of the posterior leads was required in 28 patients (Group B–15.1%) to establish the STEMI diagnosis warranting reperfusion therapy. Multivariate analysis illustrated that the 15-lead ECG was the only factor associated with achieving the STEMI diagnosis in non-conclusive 12-lead ECG cases (OR=2.43–p=0.04).Conclusion:The use of the 15-lead ECG contributes to a faster and more accurate diagnosis of STEMI, particularly in the Emergency Department, facilitating the prompt reperfusion therapy.

Introduction:Semantic Web (SW) technologies is capable of facilitating the management and sharing of knowledge and promote semantic interoperability among healthcare information systems.Aim:This article is designed to provide an overview of the SW technologies.Methods:This article was performed based on a literature review and Internet search through scientific databases such as PubMed, Scopus, Web of Science and Google Scholar.Result:The literature on SW addresses the technical and content aspects of SW technologies including description of ontology, interoperability standards in SW, creating ontology, types of ontologies, ontology editors, ontologies in healthcare.Discussion:The discussion on this forum aims to help understand the benefits of SW technologies in healthcare.Conclusion:SW promotes a shift from the “syntactic” level to the “semantic” level of services, applications, and people and finally to pragmatic level by sharing knowledge among clinicians, researchers and healthcare providers.

Introduction:The scaffold is a place for regeneration of new bone and bone tissue growths in tissue engineering applications. hADMSC is a multipotent cell which can differentiate into osteogenic, chondrogenic and adipogenic. Y-TZP has been shown to have several advantages over other ceramics because of its hard nature, namely fracture toughness and high flexural strength.Aim:This study aimed to analyze the biocompatibility of Y-TZP as a scaffold seeded with hADMSCs by in vitro analysis.Material and methods:This research involved several processes, namely Y-TZPS manufacture process, XRD examination, differentiation and characterization of hADMSC, SEM observation, and then TT.Results:The results of the XRD examination showed that Y-TZPSs had sharp peaks. It suggests that they had high crystal purity. The marked expression of the characterization of hADMSC is the positive expression of Cluster of differentiation (CD), namely CD 90, CD 73 and CD 105 above NMT and negative expressions of CD 14, CD 19, CD 34, CD 45 and also HLA-DR below NLT. The analysis of observations on the Y-TZPSs with SEM, subsequently, indicated the porosity of Y-TZPSs, as a result, the adhesion of HADMSCs occurred and grew in the porosity in the Y-TZPSs.Conclusions:Y-TZPSs with low porosity and toxicity can be able to proliferate and differentiate if seeded with hADMSC. Y-TZPSs are expected to be used as implantable biomaterials using hADMSCs with high biocompatibility.

Background:Chemical pleurodesis is generally accepted palliative dyspnea therapy and preventive of re-accumulation of pleural fluid in patients with malignant pleural effusions.Aim:Comparative analyses of efficiency of chemical pleurodesis between Video Assisted Thoracoscopic Surgery (VATS) and standard thoracostomy.Methods:From 01.01.2016-01.01.2017 at the Clinic for Thoracic Surgery of University Clinical Center (UCC) Sarajevo retrospective analysis was performed. Studied patients underwent VATS pleurodesis (G1) and standard thoracostomy pleurodesis (G2), with 60 in each group, respecting defined inclusion and exclusion criteria. Pleurodesis success was examined radiologically over the next three months.Results:Average age of all patients was 63.97±8.75 years. Gender related, 45% were men and 55% were women (F/M=1.47:1). Average hospitalization was 7.22±1.37 (G1: 6.68±1.16; G2: 7.44±1.40; Mann-Whitney U-test: p=0.0016) days. Average thoracic drainage duration was 5.45±1.69, (G1: 4.28±1.15,G2: 6.05±1.58; Mann-Whitney U-test p<0.0001) days. Pleurodesis success after first month was 98.30% in G1, 91.60% in G2 (G1 vs. G2; p=0.2089); after second month was 98.30% in G1, 78.30% in G2 (G1 vs. G2; p=0.0011) and after three months was 91.60% in G1, 63.30% in G2(G1 vs. G2; p=0.0006). Average dyspnea degree (0-5) after the pleurodesis was 0.050±0.22 in G1 and 0.62±0.76 in G2 (Mann-Whitney U-test; p=0.0001). Complication were noticed in 9.2% patients, in G1 3.3%, 15.0% in G2.Conclusion:Difference in pleurodesis efficiency between the G1 and G2 was established after second month and was even more evident after third month in favor of G1. Results show the significant statistical improvement of the degree of dyspnea in G1 as opposite to the G2.

Introduction:Nowadays in Panama, there is a lot of patient information stored in textual form which cannot be manipulated to manage adequate knowledge. There are multiple resources created to represent knowledge, including specialized glossaries, ontologies, among others. The ontologies are an important part within the scope of the recovery and organization of the information and the semantic web. Also in recent works they are used in applications of natural language processing (NLP), as a knowledge base.Aim:This research was conducted with the aim of creating a methodology that allows from a text written in NL, extract the necessary elements using NLP tools and with them create a knowledge base represented by one domain ontology and extract knowledge to help medical specialists.Material and Methods:In this study we carried out a methodology that allows the extraction of knowledge of patient clinical records, general medicine and palliative care, in order to show relevant knowledge elements to specialists. The methodology was validated with a data corpus of approximately 200 patient records.Conclusion:We have created a knowledge representation methodology, combining NLP techniques and tools and the automatic instantiation of an ontology, which can serve as a software agent for other applications or used to visualize the patient’s clinical information. The study was validated using the traditional metrics of information retrieval systems precision, recall, F-measure obtaining excellent results, and can be used as a software agent or methodology for the development of information extraction software systems in the medical domain.

Background:One of the performance measures of any educational system is the degree to which students learn their education. Academic achievement includes the acquisition of a set of skills and abilities that are acquired during the course and in decision making and the various issues of leadership of individuals. A variety of factors affect the academic success of students. The present study aims to investigate the successful student’s point of view from students of Mazandaran University of Medical Sciences in 2016-2017.Materials and methods:This cross-sectional study was conducted with an analytical approach. 595 students from all faculties of Mazandaran University of Medical Sciences and Health Services who were studying in the second semester of 2016-2017. To collect data, a researcher-made questionnaire made 144 questions, “Student Success Index” with 18 areas of reading, writing, speaking skills, listening skills, learning styles, memory, reading skills, critical thinking skills, motivation, self-esteem, personal relationships, conflict resolution, health, time management, Financial Management, Personal Purposes, Work Planning and Support Resources, each of which includes 8 fields. The Mann–Whitney U test and Kruskal-Wallis test used for analysis.Results:There is a meaningful relationship between auditory skills, reading, creative thinking and critique, motivation, personal relationships, conflict resolution, time management, personal goals, work planning, sources of support and School. )P<0.05(. Also, there is a significant relationship between the dimension of personal goals and educational level (P <0.05). In terms of personal dimensions, PhD students had lower levels than the average.Conclusion:Empowering human resources through education is possible. Obviously, with the increase in the efficiency of universities and higher education institutions, one can take a major step in the development of the country. It is suggested that in order to improve the quality of these skills among students, the teaching strategies for learning these skills should be included in the student’s curriculum, or by conducting workshops on the use of these strategies during the study period for students for improving and developing it.