Thematic tracks

Artificial Intelligence in Medicine

Every day medicine is facing new challenges: new diseases, cost reductions, new therapeutics, quick decisions and make more with less. Artificial Intelligence (AI) can play an important role in the decision making process, most concretely in the way the data of the patients are collected, treated, processed and presented as well to test and simulate new treatments, scenarios and devices. The big question to be answered is: How Artificial Intelligence can help to overcome these challenges and provide new and efficient solutions to medicine?

Business Intelligence, Data Mining, Sensing, Pervasiveness, Ubiquity and Intelligent Agents in Medicine, can contribute with new artifacts and new knowledge for health professionals. The development of AI systems has been one of the most ambitious and, not surprisingly, controversial themes in medicine. Often, healthcare professionals are septic regarding the use of these technologies, because they are afraid of losing their jobs. However, this concern is not justified. AI no longer aims the substitution of professionals by computer artifacts. AI aims to improve the usability of programs for assisting physicians in figuring out what is wrong with the patients and provide new solutions to help making better decisions. AI systems are intended to support healthcare practitioners in the normal course of their duties, assisting with tasks that rely on the manipulation of data and knowledge. In particular, these systems have for example the capacity to learn, leading to the discovery of new phenomena and the creation of medical knowledge.

This track promotes a forum to discuss and present emergent themes, new projects and ideas about how AI can contribute to the field of Medicine and, most concretely, improve patient conditions. By bringing together researchers from two distinct areas is expected to produce new scientific and technical knowledge in a particular area as is medicine.

Information technology, in general, can help improving human health and longevity. To achieve this goal innovative and intelligent software can be deployed in order to improve medical research, disease prevention, and healthcare service delivery.

The motto of this track is “artificial intelligence improves medicine” and we are inviting the community to share this vision.


Topics of Interest

Innovative and exciting works are welcome in areas including but not limited to:

Medical methodologies, architectures, environments and systems:

  • Agents for information retrieval;
  • AI in Medical Education and Clinical Management;
  • Wellbeing and lifestyle support;
  • Interoperability, Security, Pervasiveness, Ubiquity and Cloud Computing in Medicine;
  • Methodological, philosophical, ethical, and social issues of AI in Medicine;
  • Pervasive Healthcare Environments;
  • Software architectures.

Knowledge engineering and Decision Support Systems:

  • AI-based clinical decision making and Clinical Decision Support Systems;
  • Automated reasoning, Case-Based Reasoning or Reasoning with medical knowledge;
  • Business Intelligence in Health Care;
  • Clinical Data Mining;
  • Data Streaming;
  • Diagnostic assistance;
  • Expert, agent-based or knowledge-based systems;
  • Medical knowledge engineering;
  • Pervasive or Real-Time Intelligent Decision Support Systems in Critical Health Care.

Medical Applications and Devices:

  • Computational intelligence in bio- and clinical medicine;
  • Electronic Health Records (eHealth);
  • Image recognition and interpretation;
  • Intelligent devices and instruments;
  • Sensor-based applications;
  • Telemedicine and mHealth solutions;
  • Ubiquitous devices in the storage, update, and transmission of patient data;
  • Usability and acceptability.

AI in Healthcare Information Systems:

  • Autonomous systems to support independent living;
  • Healthcare System Based on Cloud Computing;
  • Intelligent Healthcare information systems;
  • Pervasive Information Systems;
  • Pervasiveness and Security in Clinical Systems;
  • Smart homes, hospitals and Intelligent Systems;
  • Simulation Computer systems.


Paper submission

Submissions must be original and not published elsewhere. Papers should not exceed twelve (12) pages in length and must adhere to the formatting instructions of the conference. Each submission will be peer reviewed by at least three members of the Program Committee. The reviewing process is double blind, so authors should remove names and affiliations from the submitted papers, and must take reasonable care to assure anonymity during the review process. References to own work may be included in the paper, as long as referred to in the third person. Acceptance will be based on the paper’s significance, technical quality, clarity, relevance and originality.


Paper Publication

All accepted papers will be published by Springer in a volume of the LNAI-Lecture Notes in Artificial Intelligence series (indexed by the Thomson ISI Web of Knowledge). The number of pages of the accepted contributions has the following limits:

  • Full Regular Papers: Contributions accepted as full papers should contain from 10 to 12 pages in its final version, according to the LNAI series formatting instructions. Extraordinarily, other two additional pages could be considered with a supplementary fee.
  • Short Papers: Contributions accepted as short papers should contain from 4 to 6 pages in its final version, according to the LNAI series formatting instructions.

All accepted papers must be presented orally the conference by one of the authors and at least one author of each accepted paper must register for the conference.

Special Issue of the Artificial Intelligence in Medicine Journal

Authors of the best papers presented at the AIM track of EPIA will be invited to submit extended versions of their manuscripts for a special issue of the “Artificial Intelligence in Medicine”, indexed at ISI Web of Knowledge (ISI impact factor JCR2013 of 1.356). Artificial Intelligence and Medicine publishes original articles from a wide variety of interdisciplinary perspectives concerning the theory and practice of artificial intelligence (AI) in medicine and health care.


Important dates

Deadline for paper submission: March 9, 2015
Notification of paper acceptance: 27, April, 2015
Camera-ready papers due: 1, June, 2015
Conference dates: September 8-11, 2015


Track Chairs

Manuel Filipe Santos
University of Minho, Portugal
Email: mfs (at)
Carlos Filipe Portela
University of Minho, Portugal
Email:cfp (at)


Programme Committee

Álvaro Silva, Abel Salazar Biomedical Sciences Institute, Portugal
Andreas Holzinger, Medical University Graz, Austria
António Abelha, University of Minho, Portugal
Antonio Manuel de Jesus Pereira, Polytechnic Institute of Leiria, Portugal
Barna Iantovics, Petru Maior University of Tîrgu-Mureş, Romania
Beatriz de la Iglesia, University of East Anglia, UK
Cinzia Pizzi, Universita’ degli Studi di Padova, Italy
Danielle Mowery, University of Utah, USA
Do Kyoon Kim, Pennsylvania State University, USA
Giorgio Leonardi, University of Piemonte Orientale, Italy
Góoran Falkman, Universitet of Skovde, Sweden
Hélder Coelho, University of Lisbon, Portugal
Helena Lindgren, Umea University, Sweden
Inna Skarga-Bandurova, East Ukrainian National University, Ukrainian
José Machado, University of Minho, Portugal
José Maia Neves, University of Minho, Portugal
Luca Anselma, University of Turin , Italy
Michael Ignaz Schumacher, University of Applied Sciences Western, Switzerland
Miguel Angel Mayer, Pompeu Fabra University, Spain
Mohd Khanapi Abd Ghani, Technical University of Malaysia, Malaysia
Panagiotis Bamidis, Aristotelian Univ. of Thessaloniki, Greece
Pedro Gago, Polytechnic Institute of Leiria, Portugal
Pedro Pereira Rodrigues, University of Porto, Portugal
Rainer Schmidt, Institute for Biometrics and Medical Informatics, Germany
Ricardo Martinho, Polytechnic Institute of Leiria, Portugal
Rui Camacho, University of Porto, Portugal
Salva Tortajada, Polytechnic University of Valencia, Spain
Shabbir Syed-Abdul, Taipei Medical University, Taiwan
Shelly Sachdeva, Jaypee Institute of Information Technology, India
Szymon Wilk, Poznan University of Technology, Poland
Ulf Blanke, Swiss Federal Institute of Technology in Zurich, Switzerland
Werner Ceusters, University at Buffalo, USA