Feedback regarding students initial pharmaceutical internship from the University of Medicine and Pharmacy, Cluj-Napoca

Introduction/Aims: The purpose of the study is to evaluate the perception of the organization, the development and the evaluation of the initial stage in the internship of students, in order to improve these activities and to establish the adequate objectives in accordance with the changes concerning the concept of modern pharmacy. Materials and methods: An online survey was made using Google Docs ® -Create Form extension. All results were accumulated and computed using Microsoft Excel ®. The questionnaire consisted of 11 questions, structured on several levels: the objectives and how they can be achieved, internship organization, the internship training (effective participation in specific activities and integration in the pharmaceutical activity), the assessment, the profile of tutor / pharmacy. The questionnaire was completed by students from the Faculty of Pharmacy, University of Medicine and Pharmacy "Iuliu Haţieganu" Cluj Napoca, Romania. Results and discussions. The study was conducted on 308 students (60% of all students from the study years II-IV. 90% of the respondents had actually participated in the internship, whilst 10% only formally participated in this activity. The main responsibilities of the students were: storage and reception of pharmaceutical products (94%, respectively 79%) and working with the receipts (57%). Most of the students appreciate that they were integrated into the work in the pharmacy, this being due largely pharmacist tutor, who expressed interest and ability in mentoring activities. They appreciated that the role of tutor requires 3-5 years of professional experience. In terms of the internship objectives, these should aim at applying the knowledge gained until the graduation year, but also familiarization with activities which might turn into applications for the coming years. 43% of students believe that only 25% of the theoretical knowledge was useful during the internship. 90 % of the total questioned considered useful to develop a practice guideline adapted to the year of study. Conclusions. The professional training of the future pharmacist’s students depends largely on experience gained by students during the internship activity. Feed-back from the students’ shows that they are aware of the usefulness of the internship, but believe the objectives must be updated and a better correlation between work in pharmacy and theoretical knowledge has to be made. A first step is to develop a practical guide adapted to each year of study. The involvement of the tutor pharmacist is also essential to the success of this activity

Machine Learning Algorithms at Myocardial Perfusion Imaging - a Preliminary Study

Introduction: A major focus of data mining process - especially machine learning researches - is to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. Since imaging techniques like MPI – Myocardial Perfusion Imaging on Nuclear Cardiology, can implicate a huge part of the daily workflow and generate gigabytes of data, there could be advantages on Computerized Analysis of data over Human Analysis: shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc.Objectives: The aim of this study relates with the evaluation of the efficacy of this methodology on the evaluation of MPI Stress studies and the process of decision taking concerning the continuation – or not – of the evaluation of each patient. It has been pursued has an objective to automatically classify a patient test in one of three groups: “Positive”, “Negative” and “Indeterminate”. “Positive” would directly follow to the Rest test part of the exam, the “Negative” would be directly exempted from continuation and only the “Indeterminate” group would deserve the clinician analysis, so allowing economy of clinician’s effort, increasing workflow fluidity at the technologist’s level and probably sparing time to patients. Methods: WEKA v3.6.2 open source software was used to make a comparative analysis of three WEKA algorithms (“OneR”, “J48” and “Naïve Bayes”) - on a retrospective study using the comparison with correspondent clinical results as reference, signed by nuclear cardiologist experts - on “SPECT Heart Dataset”, available on University of California – Irvine, at the Machine Learning Repository. For evaluation purposes, criteria as “Precision”, “Incorrectly Classified Instances” and “Receiver Operating Characteristics (ROC) Areas” were considered. Results: The interpretation of the data suggests that the Naïve Bayes algorithm has the best performance among the three previously selected algorithms. Conclusions: It is believed - and apparently supported by the findings - that machine learning algorithms could significantly assist, at an intermediary level, on the analysis of scintigraphic data obtained on MPI, namely after Stress acquisition, so eventually increasing efficiency of the entire system and potentially easing both roles of Technologists and Nuclear Cardiologists. In the actual continuation of this study, it is planned to use more patient information and significantly increase the population under study, in order to allow improving system accuracy.

Remote experimentation network - yielding an inter-university peer-to-peer e-service

The goal of this paper is to discuss the benefits and challenges of yielding an inter-continental network of remote laboratories supported and used by both European and Latin American Institutions of Higher Education. Since remote experimentation, understood as the ability to carry out real-world experiments through a simple Web browser, is already a proven solution for the educational community as a supplement to on-site practical lab work (and in some cases, namely for distance learning courses, a replacement to that work), the purpose is not to discuss its technical, pedagogical, or economical strengths, but rather to raise and try to answer some questions about the underlying benefits and challenges of establishing a peer-to-peer network of remote labs. Ultimately, we regard such a network as a constructive mechanism to help students gain the working and social skills often valued by multinational/global companies, while also providing awareness of local cultural aspects.