GT4 Technology Enhanced Medical Education and Simulation

Iraklis Paraskakis's picture
Iraklis Paraskakis
SEERC (GR) & The University of Sheffield (UK)
Meni Tsitouridou's picture
Meni Tsitouridou
Aristotle University of Thessaloniki (GR)
Conference room
Session time
Friday, June 23, 2017 - 14:00 to 15:30
Design and Evaluation of a Virtual Reality Simulation Module for Training Advanced Temporal Bone Surgery
Surgical education has traditionally relied on cadaveric dissection and supervised training in the operating theatre. However, both these forms of training have become inefficient due to issues such as scarcity of cadavers and competing priorities taking up surgeons' time. Within this context, computer-based simulations such as virtual reality have gained popularity as supplemental modes of training.
Sudanthi Wijewickrema's picture
Sudanthi Wijewickrema
University of Melbourne (AU)
Bridget Copson's picture
Bridget Copson
Yun Zhou's picture
Yun Zhou
Xingjun Ma's picture
Xingjun Ma
The University of Melbourne (AU)
Robert Briggs's picture
Robert Briggs
James Bailey's picture
James Bailey
Gregor Kennedy's picture
Gregor Kennedy
Stephen OLeary's picture
Stephen OLeary
Inductive learning of the surgical workflow model through video annotations
Surgical workflow modeling is becoming increasingly useful to train surgical residents for complex surgical procedures. Rule-based surgical workflows have shown to be useful to create context-aware systems. However, manually constructing production rules is a time-intensive and laborious task. With the expansion of new technologies, large video archive can be created and annotated exploiting and storing the expert’s knowledge.
Hirenkumar Nakawala's picture
Hirenkumar Nakawala
Politecnico di Milano (IT)
Elena De Momi's picture
Elena De Momi
Laura Erica Pescatori's picture
Laura Erica Pescatori
Anna Morelli's picture
Anna Morelli
Giancarlo Ferrigno's picture
Giancarlo Ferrigno
LiveBook: Competence Assessment with Virtual-Patient Simulations
Virtual-patient simulators play an important role in modern medical education. These simulators provide a safe environment for learning, give contextual feedback to learners, and allow the learner to move beyond the time and space constraints of traditional face-to-face medical instruction. In this paper, we present an interactive simulation system, LiveBook. This system interacts with students in natural language, and provides detailed feedback on the student's performance after a case has been studied.
Sina Jalali's picture
Sina Jalali
Eleni Stroulia's picture
Eleni Stroulia
University of Alberta (CA)
Sarah Foster's picture
Sarah Foster
Sarah Forgie's picture
Sarah Forgie
Amit Persad's picture
Amit Persad
Diya Shi's picture
Diya Shi
Implementation of process-oriented feedback in a clinical reasoning tool for virtual patients
Virtual patients (VPs) offer a safe environment to teach clinical reasoning skills, but feedback is often provided in outcome-, rather than process-oriented fashion. For complex cognitive skills, such as clinical reasoning, the process itself is often more important then the end result, especially during learning phase. We have developed a tool that can be integrated into VP systems to specifically support the clinical reasoning process and provide both, outcome- and process-oriented feedback.
Inga Hege's picture
Inga Hege
Ludwig-Maximilians-Universität München (DE)
Andrzej A Kononowicz's picture
Andrzej A Kononowicz
Michal Nowakowski's picture
Michal Nowakowski
Martin Adler's picture
Martin Adler
Novel Method for Storyboarding Biomedical Videos for Medical Informatics
We propose a novel method for developing static storyboard for video clips included with biomedical research literature. The technique uses both visual and audio content in the video to select candidate key frames for the storyboard. From the visual channel, the intra-frames are extracted using FFmpeg tool. IBM Watson speech-to-text service is used to extract words from the audio channel, from which clinically significant concepts (key concepts) are identified using the U.S. National Library of Medicine‘s Repository for Informed Decision Making (RIDEM) service.
Sema Candemir's picture
Sema Candemir
Sameer Antani's picture
Sameer Antani
U.S. National Library of Medicine / NIH (USA)
Zhiyun Xue's picture
Zhiyun Xue
George Thoma's picture
George Thoma
A Proposed Learner Activity Taxonomy and a Framework for Analysing Learner Engagement versus Performance using Big Educational Data
The inclusion of information and communication technologies in Healthcare and Medical Education is a fact nowadays. Furthermore numerous virtual learning environments have been established in order to host both educational material and learner’s online activities. Online modules in a VLE can be designed in very different ways being part of different types of courses, while different models can be used to design the course based on what the creator aims to achieve. Thus, the types and the importance of the different elements of the online course may vary a lot.
Stathis Th. Konstantinidis's picture
Stathis Th. Konstantinidis
University of Nottingham (UK)
Aaron Fecowycz's picture
Aaron Fecowycz
Kirstie Coolin's picture
Kirstie Coolin
Heather Wharrad's picture
Heather Wharrad
George Konstantinidis's picture
George Konstantinidis
Panagiotis Bamidis's picture
Panagiotis Bamidis
Aristotle University of Thessaloniki (GR)

ST1 - Ambient Assisted Living based on IoT Technologies

Dimitrios Koutsouris's picture
Dimitrios Koutsouris
National Technical University of Athens (GR)
Kostas Giokas's picture
Kostas Giokas
AiM Research Biomedical Engineering Lab NTUA (GR)
Conference room
Session time
Friday, June 23, 2017 - 11:00 to 12:30
Applied technologies and Smart Home applications in the health sector
Smart homes are no longer design concepts of the future. They are being built now, and they are having a direct impact on the lifestyles of people living in them. The aim of smart home systems is to create an environment that is aware of the activities taking place within it. Beside the healthy people, disabled people also need such systems to make their life easier, because they encounter with a lot of difficulties in their everyday life especially when they are at home.
Nikolaos Katsivelis's picture
Nikolaos Katsivelis
Athanasios Anastasiou's picture
Athanasios Anastasiou
Ourania Petropoulou's picture
Ourania Petropoulou
George Lambrou's picture
George Lambrou
National Technical University of Athens (GR)
Kostas Giokas's picture
Kostas Giokas
AiM Research Biomedical Engineering Lab NTUA (GR)
Dimitrios Koutsouris's picture
Dimitrios Koutsouris
National Technical University of Athens (GR)
A Fall Prevention System for the Elderly: Preliminary Results
The fall prevention in the elderly population is a field of growing interest. This paper presents the preliminary results of a fall prevention system based on a customized exergame program. Results show that the participants involved in the experiments evaluate positively the system usability. Moreover, in order to evaluate the efficiency of the system, a global improvement of around 8.8% has been observed in the postural response after just two sessions with the system.
Giuseppe Palestra's picture
Giuseppe Palestra
StreamVision sas (FR)
Mohamed Rebiai's picture
Mohamed Rebiai
Estelle Corutial's picture
Estelle Corutial
Kostas Giokas's picture
Kostas Giokas
AiM Research Biomedical Engineering Lab NTUA (GR)
Dimitrios Koutsouris's picture
Dimitrios Koutsouris
National Technical University of Athens (GR)
Indoor Localization: A Cost-Effectiveness vs. Accuracy Study
"Recognizing the occupants’ movement and locations within a home is a basic functionality, underlying a variety of smart-home services, including energy management, ambient environment control, and assistive-living services for seniors and people with disabilities. The outdoor-localization variant of the problem is effectively addressed with the use of GPS; however, GPS does not work well inside buildings, which makes the indoor positioning problem a very active research topic.
Parisa Mohebbi's picture
Parisa Mohebbi
Eleni Stroulia's picture
Eleni Stroulia
University of Alberta (CA)
Ioanis Nikolaidis's picture
Ioanis Nikolaidis
University of Alberta (CA)
Quality of Context Evaluating Approach in AAL Environment using IoT Technology
This paper presents an approach to the evaluation of Quality of Context (QoC) parameters in a ubiquitous Ambient Assisted Living (AAL) e-Health platform, supporting the care of people with special needs (elderly or with health problems) thus improving their quality of life. The proposal is initially verified with the Siafu simulator in an AAL scenario where the user’s health is monitored with information about blood pressure and body temperature. The research proceeded with the use of IoT technology, the e-Health Sensor Platform, a differentiated real environment.
Debora Cabral Nazario's picture
Debora Cabral Nazario
Pedro J. Campos's picture
Pedro J. Campos
Eduardo C. Inacio's picture
Eduardo C. Inacio
Federal University of Santa Catarina (BR)
Mario A. R. Dantas's picture
Mario A. R. Dantas
Robotic applications towards an interactive alerting system for medical purposes
"Social consumer robots are slowly but strongly invading our everyday lives as their prices are becoming lower and lower, constituting them affordable for a wide range of civilians. There has been a lot of research concerning the potential applications of social robots, some of which may implement companionship or proxying technology-related tasks and assisting in everyday household endeavors, among others.
Konstantinos Panayiotou's picture
Konstantinos Panayiotou
Aristotle University of Thessaloniki (GR)
Sofia E. Reppou's picture
Sofia E. Reppou
George Karagiannis's picture
George Karagiannis
Emmanouil Tsardoulias's picture
Emmanouil Tsardoulias
Aristeidis G. Thallas's picture
Aristeidis G. Thallas
Andreas L. Symeonidis's picture
Andreas L. Symeonidis
HEAR?INFO: A Modern Mobile-Web Platform Addressed to Hard-of-Hearing Elderly Individuals
In the concept of the hearing loss awareness, a modern mobile-web platform is hereby presented, aiming to offer constant online access to individuals who are hard of hearing, while presenting them regularly updated information concerning their condition. This information is presented via a specific modified interface, taking into account the special needs of the specific community. After a thorough research in GUI, the software requirements substitute or supplement the lack of integrated sound systems, with visual modifications, caption text and even specially chosen colours.
Penelope Ioannidou's picture
Penelope Ioannidou
National Technical University of Athens (GR)
Panagiotis Katrakazas's picture
Panagiotis Katrakazas
Stefanos Kollias's picture
Stefanos Kollias
Sarafidis Michail's picture
Sarafidis Michail
National Technical University of Athens (GR)
Dimitrios Koutsouris's picture
Dimitrios Koutsouris
National Technical University of Athens (GR)

GT3 Decision Support and Recommendation Systems

Alexander Astaras's picture
Alexander Astaras
American College of Thessaloniki (GR)
Daniel Sonntag's picture
Daniel Sonntag
German Research Center for AI (DE)
Conference room
Session time
Friday, June 23, 2017 - 09:00 to 10:30
Prognosis of abdominal aortic aneurysms: A machine learning-enabled approach merging clinical, morphometric, biomechanical and texture information
An effective surveillance strategy for the progression of abdominal aortic aneurysms (AAAs) may be achieved by assessing its expected growth rate in a personalized manner. Given the variety of factors with an impact on AAA growth, an integrative approach to the problem could potentially benefit from incorporating clinical and morphometric data, as well as mechanical stress characterizations. In addition, here we investigated the use of texture information on computed tomography angiography images within the AAA sac.
Fernando Garcia-Garcia's picture
Fernando Garcia-Garcia
ARTORG Center & University of Bern (CH)
Eleni Metaxa's picture
Eleni Metaxa
Stergios Christodoulidis's picture
Stergios Christodoulidis
Marios Anthimopoulos's picture
Marios Anthimopoulos
Nikolaos Kontopodis's picture
Nikolaos Kontopodis
Martina Correa-Londono's picture
Martina Correa-Londono
Thomas R. Wyss's picture
Thomas R. Wyss
Yannis Papaharilaou's picture
Yannis Papaharilaou
Christos V. Ioannou's picture
Christos V. Ioannou
Hendrik von Tengg-Kobligk's picture
Hendrik von Tengg-Kobligk
Stavroula Mougiakakou's picture
Stavroula Mougiakakou
A non-invasive medical decision support prototype system for Dermatology based on electrical impedance spectroscopy (DermaSense)
Premature detection of malignant melanoma remains the primary factor in reducing mortality from this form of cancer. During the last decade diagnostic sensitivity and specificity have improved through the utilization of new computer-based technologies, which help improve lesion selection for pathology review and biopsy. Despite these advances in melanoma diagnosis, initial detection, timely recognition and quick treatment of melanoma remain crucial.
Alexander Zogkas's picture
Alexander Zogkas
Sotiria Gilou's picture
Sotiria Gilou
Aristotle University of Thessaloniki (GR)
Inessa Kirsanidou's picture
Inessa Kirsanidou
Chrysovalantis Korfitis's picture
Chrysovalantis Korfitis
Christina Kemanetzi's picture
Christina Kemanetzi
Elizabeth Lazaridou's picture
Elizabeth Lazaridou
Panagiotis Bamidis's picture
Panagiotis Bamidis
Aristotle University of Thessaloniki (GR)
Alexander Astaras's picture
Alexander Astaras
American College of Thessaloniki (GR)
Is a Decision Support System Based on Robson's Classification Enough to Reduce Cesarean Section Rates?
The cesarean section (CS) rates are important global indicators for measuring the access to obstetric services. In 2001, Robson proposed a CS classification in ten-groups as the most appropriate to compare surgery rates. However, having a decisional support system from Robson's Classification is enough to reduce CS rates? The births analysis that occurred in 2016, inside a public hospital maternity, showed 1,946 deliveries of which 35.7% were CS with a positive growth trend (R2 = 0.137).
Juliano Gaspar's picture
Juliano Gaspar
Universidade Federal de Minas Gerais (BR)
Zilma Reis's picture
Zilma Reis
Juliana Barra's picture
Juliana Barra
Design and Development of a Mobile Decision Support System: Guiding Clinicians Regarding Law in the Practice of Psychiatry in Emergency Department
Decision-making in an emergency department needs to be efficient. It does not allow observation of the patient for a prolonged period of time, especially if the patients harm themselves or others, or refuses treatment. This includes suicidal, violent, intentional self-inflicted or non-consenting to treatments’ patient. Clinicians have to quickly decide whether to call the police, admit the patient to the psychiatric ward, according to recommended, predefined procedures.
Soudabeh Khodambashi's picture
Soudabeh Khodambashi
Norwegian University of Science and Technology (NO)
Florentin Moser's picture
Florentin Moser
Jon Atle Gulla's picture
Jon Atle Gulla
Pekka Abrahamsson's picture
Pekka Abrahamsson
Integrated decision support by combining textual information extraction, facetted search and information visualisation
This work focusses on our integration steps of complex and partly unstructured medical data into a clinical research database with subsequent decision support. Our main application is an integrated facetted search tool, followed by information visualisation based on automatic information extraction results from textual documents. We describe the details of our technical architecture (open-source tools), to be replicated at other universities, research institutes, or hospitals.
Daniel Sonntag's picture
Daniel Sonntag
German Research Center for AI (DE)
Hans-Jurgen Profitlich's picture
Hans-Jurgen Profitlich
Predicting Sepsis Biomarker Progression under Therapy
Sepsis is a serious, life-threatening condition that presents a growing problem in medicine and health-care. It is characterized by quick progression and high variability in the disease manifestation, so treatment should be personalized and tailored to fit individual characteristics of a particular subject. That requires close monitoring of the patient's state and reliable predictions of how the targeted therapy will affect sepsis progression over time.
Ivan Stojkovic's picture
Ivan Stojkovic
Temple University (USA)
Zoran Obradovic's picture
Zoran Obradovic
Temple University (USA)