7th International Conference
Information Technology in Biomedicine

Special Sessions

Medical Data Science

Medicine and Data Science are revolutionary and rapidly evolving disciplines presenting together the most signi cant potential for the future of helthcare. The new technologies, mobile devices, sensors, AI-powered applications, they all give the new meaning to optimization of clinical processes especially in times of demographic changes leading to society aging. The machine learning algorithms can be used to process large volumes of various, health-related data and draw a complex map of ones physical and mental condition, provide personalized information and experience or suggest prevention programmes and therapeutic interventions resulting in an active and healthy lifestyle.

The ITiB Special Session on Medical Data Science aims at attracting original manuscripts reporting on scienti c approaches, especially pattern recognition and machine learning based algorithms for interpretation of health-related, sensory data and ICT solutions towards promoting active and healthy lifestyle. More specifi cally, the thematic scope of the special session includes, but is not limited to, the following aspects:

  • pattern recognition and machine learning algorithms for interpretation of health-related data,
  • sensor-based physical activity assessment,
  • sensor-based cognitive activity assessment,
  • sensor-based emotion recognition,
  • sensor-based therapy assistance,
  • multimodal sensory data interpretation,
  • automatic gesture and gait analysis,
  • software architectures for medical data processing and interpretation,
  • sensory systems and data analysis towards Active and Assisted Living in aging society,
  • IT and ICT-based personalized intervention programmes,
  • ethical, legal and social implications of medical data science.

Special Session Organizers:

Marcin Grzegorzek, Universität zu Lübeck, Germany
Przemysław Łagodziński, University of Economics in Katowice, Poland

E-Mail: przemyslaw.lagodzinski(at)ue.katowice.pl

Call for papers




Quantitative Data Analysis in Medical Diagnosis

Medical imaging has taken advantage of several decades of intense development. This is accompanied by a significant progress in the field of image processing methods that provide physicians with a large amount of quantitative diagnostic information. This session aims to bring together experts working in image processing and analysis, pattern recognition and computer vision who collaborate with clinicians and develop computer aided imaging diagnosis methods to improve patient care. This session will seek original and unpublished research work on the following topics:

  • detection and diagnosis support systems;
  • artificial intelligence for medical data analysis, recognition, and retrieval;
  • biomedical image registration, visualization, and modelling.

Special Session Organizers:

Michał Strzelecki, Łódź University of Technology, Poland

E-Mail: michal.strzelecki(at)p.lodz.pl




Analytics in Action on SAS Platform

Technics like cognitive computing, deep learning, natural language processing, and machine learning combined with scalable, high performance SAS platform in healthcare applications can improve patient care. Computer systems can perform reliably, without fatigue, 24/7.

The session is dedicated to new systems and method connected with early warning on hard-to-detect conditions using image recognition, automated, personalized patient engagement, physician support for diagnosis and treatment course recommendations, genomics and many others.

A special focus will be put on applications with SAS as computing platform.

E-Mail: dominik.spinczyk(at)polsl.pl




Data Mining Tools and Methods in Medical Applications

Medical data are unique in several ways, resulting both from their - often heterogeneous - acquisition process and from their particular significance for patients and physicians. As a result, extraction of patterns and knowledge from medical records requires special care and application of appropriate tools and processing schemes. This session will cover a broad range of medical data mining approaches in diagnostic applications and decision support systems, including - but not limited to:

  • statistical methods,
  • machine learning and artificial intelligence tools,
  • data pre/postprocessing,
  • feature selection and transformation,
  • classification,
  • pattern recognition,
  • outlier detection.

Special Session Organizers:

Adam Wojciechowski, Łódź University of Technology, Poland
Bartłomiej Stasiak, Łódź University of Technology, Poland

E-Mail: bartlomiej.stasiak(at)p.lodz.pl




Biocybernetics in Physiotherapy

Restoring and maintaining a patient’s good quality of life, especially after serious injuries caused by i.e. stroke, requires that medical procedures should be combined with appropriate physiotherapeutic treatment. Physiotherapists supported by a biocybernetic system could work more efficient, which would lead to shorter and more effective therapies.

The aim of this session is to present original works, that concerns biocybernetics in physiotherapy, in particular in the following areas:

  1. Innovative physiotherapy procedures,
  2. Data processing and reasoning/advisory systems in rehabilitation process support
  3. Anthropometric systems in patients rehabilitation

Special Session Organizers:

Andrzej W. Mitas, Silesian University of Technology, Poland

E-Mail: andrzej.mitas(at)polsl.pl




In order to submit a paper for the special session please log in to the SOK system.