|11th March,2013||Launch of Contest|
|8th April, 2013||Last Date for Registration of Applicant|
| 10th April, 2013
|Result Submission (Segmentation Results)|
Introduction 2008 [pdf]
Modelling [pdf]Introduction (Zlatko Trajanoski) [pdf]
Introduction to SVM (Vojislav Kecman) [pdf]
Basics of Support Vector Machines (Vojislav Kecman) [pdf]
Gene Expression Clustering (Alexander Sturn) [pdf]
Neural Networks (Zlatko Trajanoski) [pdf]
PCA (Zlatko Trajanoski) [pdf]
SOM (Zlatko Trajanoski) [pdf]
Decision Trees (Zlatko Trajanoski) [pdf]
Introduction to Probability Theory (Fatima Sanchez Cabo) [pdf]
Introduction to Statistical Inference (Fatima Sanchez Cabo) [pdf]
ELGA and eHealth (Karl Pfeiffer) [pdf]
Combined document (contains all of the documents above) [pdf]
MeetWithAnExpert.ppt MeetWithAnExpert.ppt.pdf Lecture25-Prototyping.ppt Lecture26-Prototyping.ppt Lecture29-CogWT.docx Lecture29-CogWT.pdf
Clinical informatics is a method of organizing information in the health care industry. It blends information technology, computer science and biomedical informatics. Clinical informatics is a field that is constantly striving to make information more accessible in the simplest way. It involves storing, managing and accessing important health records.
Clinical informatics uses technology and computers to store data at an institution such as a hospital, doctor’s office or other health care facility. Since there are so many papers and files to process at any medical setting, an efficient system for keeping track of it all is required. Medical informatics becomes a way to organize and process the information. Examples of information stored in health informatics include disease research, patient backgrounds, statistics and treatment plans.
Biomedical informatics, as a scientific discipline, has its roots in the early 1970s. It encompasses the fields of bioinformatics, medical imaging, health informatics, and several other disciplines. In recent years, this biological field has experienced explosive growth, due to public access to massive amounts of data generated from the Human Genome Project. A host of other complementary research efforts have also contributed to the knowledge base. This synergistic blend of multiple branches of biology, combined with information technology and knowledge, has enabled researchers and clinicians to utilize an array of information to advance biological research and healthcare.