Shelda Sajeev

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Shelda Sajeev

Dr

  • Source: Scopus
  • Calculated based on no. of publications stored in Pure and citations from Scopus
20132021

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Personal profile

Personal profile

Dr Shelda Sajeev is a senior lecturer (Master of Business Information Systems), Research Fellow, and Machine Learning Cluster Lead at Torrens University's Centre for Artificial Intelligence Research and Optimisation. She has 13+ years’ experience in industry, teaching, and research with expertise in artificial intelligence, machine learning, medical image analysis, image processing, and data analytics. Her current research foci are building disease risk and diagnosis prediction models for cardiovascular disease, cardiac rehab, frailty and corneal disorders. In addition, she is  developing an automated model for predicting risk for 30-day and 12-month myocardial infarction and mortality among patients presenting to the emergency department with chest pain or suspected ACS using machine learning. Exploring methods to generate synthetic health data and techniques for validating them is another priority. She is also looking into optimisation techniques to improve medical image analysis, like image enhancement, segmentation, and feature engineering.

 

Research interests

  • Data Science
  • Artificial Intelligence
  • Machine Learning 
  • Medical Image Anlaysis
  • Image Processing
  • Pattern Recognition
  • Texture Analysis
  • Feature Engineering 
  • Disease risk prediction and diagnosis using machine learning (heart disease, diabetes, frality, cancer...)

Education/Academic qualification

Image processing and Machine Learning, PhD, Flinders University

Award Date: 26 Jul 2019

Computer Science and Engineering, Master, Visvesvaraya Technological University

Award Date: 10 May 2013

Computer Science and Engineering, Bachelor

Award Date: 20 May 2005

External positions

Postdoctoral Researcher at Flinders Digital Health Research Center , Flinders University

Jul 2018 → Feb 2021

Research Assistant at Flinders Digital Health Research Center

Jul 2017 → Jul 2018

Casual Academic at College of Science and Engineering , Flinders University

Jan 2014 → Jul 2018

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  • 101 Citations
  • 3 h-Index
  • 10 Conference contribution
  • 2 Article
  • 1 Chapter
  • 1 Review article

  • Classifying infective keratitis using a deep learning approach

    Sajeev, S. & Prem Senthil, M., 1 Feb 2021, Proceedings of the Australasian Computer Science Week Multiconference 2021, ACSW 2021. Stanger, N. & Joachim, V. L. (eds.). Association for Computing Machinery (ACM), 3437388. (ACM International Conference Proceeding Series).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

    1 Citation (Scopus)

  • Predicting australian adults at high risk of cardiovascular disease mortality using standard risk factors and machine learning

    Sajeev, S., Champion, S., Beleigoli, A., Chew, D., Reed, R. L., Magliano, D. J., Shaw, J. E., Milne, R. L., Appleton, S., Gill, T. K. & Maeder, A., 2 Mar 2021, In: International Journal of Environmental Research and Public Health. 18, 6, p. 1-14 14 p., 3187.

    Research output: Contribution to journal › Article › peer-review

    Open Access
    3 Citations (Scopus)

  • Mammographic mass identification in dense breasts using multi-scale analysis of structured micro-patterns

    Sajeev, S., Bajger, M., Lee, G., Muramatsu, C. & Fujita, H., 1 Jan 2020, 15th International Workshop on Breast Imaging, IWBI 2020. Bosmans, H., Marshall, N. & Van Ongeval, C. (eds.). SPIE, 1151323. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 11513).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

  • Cardiovascular Risk Prediction Models: A Scoping Review

    Sajeev, S. & Maeder, A., 29 Jan 2019, Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2019. Association for Computing Machinery (ACM), a21. (ACM International Conference Proceeding Series).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

    3 Citations (Scopus)

  • Deep Learning to Improve Heart Disease Risk Prediction

    Sajeev, S., Maeder, A., Champion, S., Beleigoli, A., Ton, C., Kong, X. & Shu, M., 1 Jan 2019, Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting - 1st International Workshop, MLMECH 2019, and 8th Joint International Workshop, CVII-STENT 2019, Held in Conjunction with MICCAI 2019, Proceedings. Liao, H., Wang, G., Liu, Y., Ding, Z., Balocco, S., Zhang, F., Duong, L., Phellan, R., Zahnd, G., Albarqouni, S., Demirci, S., Breininger, K., Moriconi, S. & Lee, S-L. (eds.). Springer Gabler, p. 96-103 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11794 LNCS).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

    3 Citations (Scopus)
View all 14 research outputs
View all 8 prizes