Hossein Mohammadhassanzadeh

Hossein Mohammadhassanzadeh


Hossein graduated with a master’s degree in Information Technology Engineering at Amirkabir University of Technology in Tehran, Iran. In his master’s thesis, he developed a context-based trust inference mechanism in social networks. In that project, he leveraged Natural Language Processing (NLP) techniques to extract users’ similarities to infer trust values.

Hossein is now a doctoral candidate in Computer Science at Dalhousie University. In his PhD dissertation he is developing a semantics-based data analytics framework to improve medical knowledge discovery and decision support.

Trainee Profile

CNODES Trainee from 2016 to Present
This experience has convinced me that integrating computer science and healthcare can deliver valuable impacts and offer novel contributions to the health context.

In addition to his PhD thesis work under the supervision of Dr. Raza Abidi, Hossein is working on a CNODES project under the supervision of Dr. Ingrid Sketris and Dr. Samuel Stewart in the College of Pharmacy at Dalhousie University. This project provides him a unique opportunity to pursue knowledge translation research and apply his knowledge of Natural Language Processing and text mining to pharmacy research. Hossein presented this research at the 2017 International Conference for Pharmcoepidemiology and Therapeutic Risk Management (ICPE) in Montreal, Quebec.

The following interview with Hossein is from September, 2017 –  shortly after he presented at the conference.

Can you give us a short summary of the research that you presented at ICPE and why it is important?

The acne medication isotretinoin increases the risk of miscarriage and fetal abnormalities when taken during pregnancy. A CNODES study revealed the adherence to pregnancy prevention guidelines while using isotretinoin was poor.

In our research study, we aimed to better understand how the media present pharmacoepidemiological research using the CNODES isotretinoin study as the case study. We used Natural Language Processing (NLP) to examine the media uptake of the CNODES study on isotretinoin safety. With this research project, we hope analyzing media using NLP and readability techniques can help determine communication effectiveness and uptake of drug safety issues.

Tell us about your experience presenting at ICPE. What did you gain from it? What was the highlight of the conference for you?

As a computer scientist who is fairly new to the field of pharmacoepidemiology, there is much that I need to learn about pharmacy informatics. In addition to the opportunity to present our paper and receive feedback from other attendees, participating in the ICPE 2017 was an excellent opportunity to meet experts, researchers and professionals in the field, and learn more about pharmacoepidemiology. The pre-conference workshops delivered a great introduction to the field for me. Moreover, the networking opportunity, meeting with students from different disciplines and making new friends from different countries was a bonus!

What excites you the most about the research you are doing or hope to do in the future?

Our preliminary results show there is an inefficiency in communicating the findings of scientific studies to the target population. For example, in the case of the CNODES isotretinoin study, high readability levels of the media articles, limits its understandability and comprehensibility by the audience. I will be thrilled if our research can help researchers to communicate more effectively with patients.

In an ideal world, where would you like to be career-wise in five years?

I have always been interested in working with data, digging into it and finding actionable insights and unexplored associations. Over the past few years, I have been engaged with different health projects, and have gained knowledge about medical challenges, as well as innovative, trending computational solutions addressing those issues. This experience has convinced me that integrating computer science and healthcare can deliver valuable impacts and offer novel contributions to the health context.

After graduation, I would like to continue my professional career as a data scientist. I prefer to be involved with inter-disciplinary projects in advancing knowledge technologies and innovative knowledge-centric solutions targeting healthcare enterprises.

How has CNODES impacted your studies or career trajectory?

Being a trainee of the Atlantic node of the CNODES has provided me the opportunity to pursue research in the fields of pharmacy informatics and pharmacoepidemiology. I am discovering new areas, have met new people, and joined a team that I thoroughly enjoy working with.

Outside of work and studies, what is one thing that you are really passionate about?

I really love to cook, especially for my family and friends. I enjoy trying out new foods, new tastes, new recipes and experimenting with different ingredients.

Is there anything else you’d like to share about yourself or your work?

I would like to thank CNODES for giving me the opportunity to be a trainee and also for featuring me. I am also thankful to Dr. Sketris for trusting me, and my colleagues in our wonderful team, Sam Stewart, Robyn Traynor and Susan Alexander for being supportive and encouraging.