Anam Haq

Research topic: Comprehensive Framework for Clinical Data Fusion (image and non-image information) 

Home University: Poznan University of Technology (PUT)

Host University: Universitat Politècnica de Catalunya (UPC)

Advisor (Home University): Szymon Wilk (PUT)

Advisor (Host University):  Alberto Abelló (UPC)    

 

Research Interests: Medical Image Processing, Clinical Decision Support Systems, and Machine Learning, Artificial Intelligence, Data Analysis, and Data Science

EDUCATION

March 2018 to the present:

Doctoral Candidate IT4BI. Polytechnic University of Catalonia (UPC), Barcelona, Spain

October 2016 to Feb 2018:

Doctoral Candidate IT4BI. Poznan University of Technology, Poznan, Poland

September 2011- May 2014:

MS, Computer Engineering. College of Electrical and Mechanical Engineering (CEME), National University of Sciences and Technology, Rawalpindi Pakistan

Thesis title: “Automated Detection of Wet Aged Related Macular Degeneration using Optical Coherence Tomographic Images”

RESEARCH

Clinical data is characterized not only by its constantly increasing volume but also by its diversity. Information collected in clinical information systems such as electronic health records is highly heterogeneous and it includes structured laboratory and examination results, unstructured clinical notes, images, and more often genetic data. This heterogeneity poses a significant challenge when constructing diagnostic and therapeutic decision models that should use data from all available sources to provide comprehensive support. A possible response to this challenge is offered by the concept of data fusion and associated techniques.