Sessions

Patients' remote monitoring platforms can be enhanced with intelligent recommendations and gamification functionalities to support their adherence to care plans. The current paper aims to present a methodology for creating personalized recommendations, which can be used to improve patient remote monitoring and care platforms. The current pilot system design is aimed to support patients by providing recommendations for Sleep, Physical Activity, BMI, Blood sugar, Mental Health, Heart Health, and Chronic Obstructive Pulmonary Disease aspects. The users, through the application, can select the types of recommendations they are interested in. Thus, personalized recommendations based on data obtained by the patients’ records anticipated to be a valuable and a safe approach for patient coaching. The paper discusses the main technical details and provides some initial results. 

Artificial intelligence (AI) can potentially contribute to solutions to some of the major challenges facing healthcare systems around the world. However, the development of new AI applications does not guarantee that they will be routinely used in clinical practice. It is well established in implementation and innovation research that the introduction of new technology is associated with various forms of obstacles and resistance. This contributes to delayed and variable application and a high risk of losing the potential value they can bring to the healthcare system in terms of quality, safety, accessibility and optimization. In this presentation, we provide an overview of state of the art regarding the implementation of AI applications in healthcare today. We also suggest ways forward, how to develop successful strategies for implementation and work structured with implementation processes.

How wearables will revolutionize eHealth.

EHDS - Status and negotiation process

Review of the potential of using machine learning for the integration of medical data.

This workshop is designed to provide a comprehensive overview of the EFMI accreditation process, its benefits and importance, key requirements, and criteria, and tips for a successful accreditation application. Aimed at universities and institutions looking to attain EFMI accreditation, this workshop will provide valuable insights and guidance. Our experienced speakers will share their expertise, personal experiences with their master’s accreditation, and answer any questions participants may have about the process.

The Health Data Guide is intended to provide an overview of managing health data effectively so that the goals of improving the health of individuals can be more easily realized. Part One should provide a brief overview of the health data area and insights into a series of typical hurdles to overcome and ditches to avoid. It should provide the newcomer to the area with sufficient orientation to facilitate the discussion with various experts and partners. The more detailed Part Two is under development.