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Brendan E. Odigwe

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • eess.IV1
  • q-bio.QM1

identity via Semantic Scholar / OpenAlex

most citedModelling of Sickle Cell Anemia Patients Response to Hydroxyurea using Artificial Neural Networks

4 citations · 6 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2021

Application of Machine Learning in Early Recommendation of Cardiac Resynchronization Therapy

Brendan E. Odigwe, Francis G. Spinale, Homayoun Valafar

Heart failure (HF) is a leading cause of morbidity, mortality, and health care costs. Prolonged conduction through the myocardium can occur with HF, and a device-driven approach, t…

eess.IV2019★ 2 cited

Automated Analysis of Femoral Artery Calcification Using Machine Learning Techniques

Liang Zhao, Brendan Odigwe, Susan Lessner +3

We report an object tracking algorithm that combines geometrical constraints, thresholding, and motion detection for tracking of the descending aorta and the network of major arter…

q-bio.QM2019★ 4 cited

Modelling of Sickle Cell Anemia Patients Response to Hydroxyurea using Artificial Neural Networks

Brendan E. Odigwe, Jesuloluwa S. Eyitayo, Celestine I. Odigwe +1

Hydroxyurea (HU) has been shown to be effective in alleviating the symptoms of Sickle Cell Anemia disease. While Hydroxyurea reduces the complications associated with Sickle Cell A…

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