Name: Hossein Naseri.
Most recent degree: MSc Physics
Level at MPU: PhD.
Email: hossein.naseri [at] mail.mcgill.ca
Supervisor(s): Dr. John Kildea
Research interests: Bioinformatics, precision medicine in oncology
The majority of the cancer patients suffer from severe pain at some stage of their illness. In most cases, cancer pain is underestimated by clinical staff and is not properly managed until it reaches a severe stage. This inadequate management of pain affects cancer patients both physically, and mentally. Detecting cancer pain in its early stage is a challenging task but it could save cancer patients from suffering from severe distress. The objective of this research project is to detect pain at an early stage by analyzing patients’ medical images. Development of an algorithm to do this can be achieved by combining two computer science techniques: one that allows us to gather information about pain from medical notes, and one that extracts information from medical images. We will use the first technique to extract and quantify pain intensity recorded in patients' medical notes. The second technique will be employed to analyze radiographic images of cancer patients to extract information about their tumors (such as tumor volume and shape). Then, we will implement mathematical techniques to model the relationship between identified tumor features and extracted pain intensities. Finally, we will use pain scores that are directly collected from thousands of future cancer patients via a mobile app that has been developed in our group (opalmedapps.com) to validate our model. A significant and novel application of our model will be to predict pain using the radiographic images of cancer patients before they experience it. This will help to improve the quality of life of cancer patients.
Naseri Hossein, and Kildea John. (2019). Feasibility of Using Natural Language Processing to Extract Cancer Pain Score from Clinical Notes. Journal of the European Society for Radiotherapy and Oncology. CARO-ASM 2019 Annual Meeting, 196(S65),
Predoi-Cross A, Hashemi R, Devi VM, Naseri H, Smith MAH. (2018). Analysis of Fourier transform spectra of N2O in the ν3 band for atmospheric composition retrievals. Canadian Journal of Physics. 96(4): 454-464.
Predoi-Cross A, Esteki K, Rozario H, Naseri H, Latif S, Thibault F, Devi VM, Smith MAH, Mantz AW. (2016). Theoretical and revisited experimentally retrieved He-broadened line parameters of carbon monoxide in the fundamental band. Journal of Quantitative Spectroscopy and Radiative Transfer. 184: 322-340.
Seyed-Mahmoud B, Morad A, Kamruzzaman M, Naseri H. (2015). Effects of density stratification on the frequencies of the inertial-gravity modes of the Earth's fluid core. Geophysical Journal International. 202: 1146-1157.
Hashemi R, Povey C, Derksen M, Naseri H, Garber J, and Predoi-Cross A. (2014). Doppler broadening thermometry of acetylene and accurate measurement of the Boltzmann constant. The Journal of Chemical Physics 141, 214201 (2014). 141: 214-201.
Ruth & Alex Dworkin Scholarship, Faculty of Medicine (2020-2021)
Mitacs Research Training Award (2019)
RI-MUHC Studentship (2019-2020)
McGill Graduate Excellence Fellowship (2018)
U of Lethbrige GSA Travel Award (2014)
U of Lethbrige SGS Scholarship (2013-2015)
Alberta Innovates technology award (AITF) (2014)
Microsoft ImagineCup Innovation Award (2014)