Sessions

May 21 – 24, 2023
Connect4Health via NordXDataspace at Vitalis
The Connect4Health healthcare connectathon using NordxDataspace aims to promote digital wallets and Solid pods as a data intermediary through a trusted data intermediation service to enable organisations to become part of the European Health Data Space while ensuring data privacy, human-centric use of personal data and digital rights. 

The MIE conference has always been a hub for innovation and cutting-edge technology. This year was no exception several demonstrators showcase their unique solutions to healthcare problems. Use the opportunity to take a closer look at some of the most striking demonstrators present at the conference, highlighting their diversity and the potential impact they could have on various healthcare-related challenges

In this session, we will present an overview of a study about the use of IoT in schools. We engaged with IoT experts to discuss how IoT-based solutions could help to improve the health and well-being of students, teachers, and other school staff. We present the main themes that surfaced in expert interviews, containing ideas on how IoT could help fulfill the needs and requirements of school personnel and students.

A great pitch@vitalisAt A great pitch@vitalis, the most innovative Healthtech companies will showcase new digital solutions in healthcare. Attendees can listen to short pitches where approximately 10 companies present their innovations, followed by questions from a distinguished panel. The participating companies will be announced in early May. We welcome you to join us for this engaging event with high energy and excitement!When: Tuesday, May 23, from 11 am to 12:30 pm
Where: Vitalis Matchmaking and Event Area (in the exhibition)
 
A conference pass is not required as it is included in the exhibition ticket.

EIT Health is a strong European network in healthcare education, research, technology, business creation and corporate and social innovation. EIT Health is a unique concept for widening participation and outreach across Europe connects the different activities in innovation, business creation, and education towards common targets.

Patients with cancer starting invasive treatment programs often develop depression that physicians struggle to recognize at an early stage. We developed a prediction model for early identification of patients at risk for depression within the first month of chemo- or radiotherapy treatment to assist physicians and healthcare workers. 

Digital health technologies (DHTs) have a great potential to help citizens and health professionals address preventable risk factors associated with diseases and illnesses that shorten human lives. DHTs can facilitate early detection, treatment, management of chronic conditions and support healthy ageing. DHTs also make it possible to shift from reactive to active and holistic delivery of health care services by empowering citizens in accessing their personal health data, monitoring, and managing their own health, based on their own preferences.

The panel-discussion will focus on the societal perspective of how to ensure introduction of useful and affordable solutions in social / health care?Is there an overlap between evaluation frameworks and the MDR?What type of evidence of usefulness should be required at different stages of implementation?Is there a need to evaluate the effectiveness of implemented solutions in real-life?How do we ensure affordability / cost-effectiveness?

The automatic de-identification of clinical narrative text offers efficient patient data privacy protection and eases reuse of clinical data. CliniDeID applies an ensemble method combining deep and shallow machine learning with rule-based algorithms and is released as free and open-source solution to de-identify unstructured clinical text with high accuracy. It was recently evaluated with a selection of clinical text corpora and reached high sensitivity and positive predictive value.

Autism spectrum disorder (ASD) is a developmental disability caused by differences in the brain regions. Analysis of differential expression (DE) of transcriptomic data allows for genome-wide analysis of gene expression changes related to ASD. De-novo mutations may play a vital role in ASD, but the list of genes involved is still far from complete. Differentially expressed genes (DEGs) are treated as candidate biomarkers and a small set of DEGs might be identified as biomarkers using either biological knowledge or data-driven approaches like machine learning and statistical analysis. In this study, we employed a machine learning-based approach to identify the differential gene expression between ASD and Typical Development (TD). The gene expression data of 15 ASD and 15 TD were obtained from NCBI GEO database. Initially, we extracted the data and used a standard pipeline to preprocess the data. Further, Random Forest (RF) was used to discriminate genes between ASD and TD. We identified the top 10 prominent differential genes and compared them with the statistical test results. Our results show that the proposed RF model yields 5-fold cross-validation accuracy, sensitivity and specificity of 96.67%. Further, we obtained precision and F-measure scores of 97.5% and 96.57%, respectively. Moreover, we found 34 unique DEG chromosomal locations having influential contributions in identifying ASD from TD. We have also identified chr3:113322718-113322659 as the most significant contributing chromosomal location in discriminating ASD and TD. Our machine learning-based method of refining DE analysis is promising for finding biomarkers from gene expression profiles and prioritizing DEGs. Moreover, our study reported top-10 gene signatures for ASD may facilitate the development of reliable diagnosis and prognosis biomarkers for screening ASD.Keywords: Gene expression data, NCBI, Autism Spectrum Disorder, Random Forest, Statistical test

The introduction of healthtech solutions has proven, by now, that it is having an impact in the main challenges that healthcare systems have in front of them-Democratization of care at a fraction of the cost. However, it is still challenging to assess the contribution each and every healthtech solution brings to society in an aggregated way. Would a metric like QALY (Quality-Adjusted Life year) and its use in healthtech help tackle this challenge?  Come and participate in a discussion, where we will share QALY results obtained for a variety of HealthTech solutions (updated results of a test asking the same question) as food for thought. Let’s discuss together: Is QALY viable for decision making to implement healthtech solutions?  -What are the uses QALY could have and what’s its potential? - Could an aggregated QALY help us measure impact?  Let’s find a path towards the adoption of Healthtech together!

The future success of moving to a smart hospital is understanding the risk. Risk should be an open transparent conversation between stakeholders of the future hospital. With an increase in interconnected devices that allow for more remote care the protection of the central brain of the hospital is critical. Change takes time and education. If we consider current cyber threats that healthcare as an industry faces one might ask what does it really mean to be secure? Security is not a permanent achievable state, it is temporal and fluid. Technology in healthcare is ever-changing and along with that there should be a clear understanding of the risks. Breaches happen almost daily around the world specifically within healthcare. As a highly targeted industry, how do we effectively deal with these breaches, what is the estimated downtime? This talk explores the current state of responses to breaches, and potential solutions with a focus on education and disaster planning for not if but when it happens.

The shortage of skilled nursing personnel is – among other reasons – due to the low attractiveness of the profession, comprising high workloads and atypical working hours. Studies show that speech-based documentation systems increase documentation efficiency and satisfaction of physicians. This paper describes the development process of a speech-based application to support nurses, according to the user-centered design approach. User requirements were collected based on interviews (n=6) as well as observations (n=6) in three institutions and were evaluated by means of qualitative content analysis. A prototype of the derived system architecture was implemented. Based on a usability test (n=3), further potentials for improvement were determined. The resulting application enables nurses to dictate personal notes, share them with colleagues and transmit notes to the existing documentation system. We conclude that the user-centered approach ensures the extensive consideration of the nursing staff’s requirements and shall be continued for further development.

The MIE conference has always been a hub for innovation and cutting-edge technology. This year was no exception several demonstrators showcase their unique solutions to healthcare problems. Use the opportunity to take a closer look at some of the most striking demonstrators present at the conference, highlighting their diversity and the potential impact they could have on various healthcare-related challenges