Pradeep Reddy Raamana

ORCID iD
orcid.org/0000-0003-4662-0558
  • Also known as
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Pradeep Kumar Ramana

Sources:
Pradeep Reddy Raamana (2014-07-22)

  • Country
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Canada

Sources:
Pradeep Reddy Raamana (2016-01-24)

  • Keywords
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medical imaging,

Sources:
Pradeep Reddy Raamana (2017-01-19)

machine learning,

Sources:
Pradeep Reddy Raamana (2017-01-19)

neurodegenerative disorders,

Sources:
Pradeep Reddy Raamana (2017-01-19)

informatics,

Sources:
Pradeep Reddy Raamana (2017-01-19)

high performance computing

Sources:
Pradeep Reddy Raamana (2017-01-19)

  • Websites
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Google Scholar

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Pradeep Reddy Raamana (2014-07-22)

Homepage / Blog

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Pradeep Reddy Raamana (2014-07-22)

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ResearcherID: C-5018-2017

Sources:
ResearcherID (2017-02-11)

Biography

Hello, There! This is Pradeep. I am currently working as a Postdoctoral fellow at the Rotman Research Institute, Baycrest affiliated with University of Toronto. I am currently working on study and development of optimal and reproducible fMRI preprocessing workflows with Prof. Stephen Strother. I am also interested in the development of machine learning techniques for medical image analysis. In particular, I worked on the development of statistical learning techniques for the early detection of Alzheimer’s disease as well as differential diagnosis of various neurodegenerative diseases. During my Ph.D., I worked with Prof. Mirza Faisal Beg. Some of my developments include novel imaging biomarkers, called ThickNet features (http://www.sciencedirect.com/science/article/pii/S0197458014005521), based on graph-theoretical network analysis of inter-regional covariation in cortical thickness, which show promise for the early detection of Alzheimer's disease. You can find the related publications in this direction here (http://www.sciencedirect.com/science/article/pii/S2213158214001417) and here (http://ieeexplore.ieee.org/abstract/document/7552334/). Another exciting area of research I am working on is the development of imaging-based biomarkers for the subclassification of MCI (classification of MCI subtypes), which can potentially lead to earlier screening of Alzheimer's disease. A publication in this direction can be found here: http://journal.frontiersin.org/Journal/10.3389/fneur.2014.00076/abstract . I have also worked on developing multi-class differential diagnosis techniques, that can pave way for minimized misdiagnosis. One such application I worked is on three-class differential diagnosis between Alzheimer's disease, Frontotemporal disease and healthy controls. A publication in this direction can be found here: http://journal.frontiersin.org/Journal/10.3389/fneur.2014.00071/abstract.
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