My research
I made significant contributions to research related to machine learning and AI in the medical field, culminating in 6 scientific articles and 4 conference presentations.
Conferences and scientific papers
I worked as an author of the following conferences papers:
- Preserving the tropical branches of the tree of life: the genome bank of Pontificia Universidad Católica del Ecuador. - 2018 Viena.
- Exploring Survival Models Associated with MCI to AD Conversion: A Machine Learning Approach. - 2019 Chicago.
- Ensemble of SVM, Random-Forest and the BSWiMS Method to Predict and Describe Structural Associations with Fluid Intelligence Scores from T1-Weighed MRI - 2019 China.
- Prediction of MCI to AD risk of conversion survival models: qMRI vs CSF measures and cognitive assessments. - 2020 Houston.
Go to my profile on Google scholar to more about my research
Cox Benchmarking
2016-2018
Algorithm for R
The CoxBenchmarking implementation is a computer-based benchmarking algorithm that compares survival models that were built using various machine learning strategies. It was developed as an extension of the FRESA.CAD package ( CRAN and use the Random Holdout Cross-Validation from the package. CoxBenchmarking provides an algorithm that generates eleven different survival models by selecting features from ML-based techniques: 6 wrappers and 5 filters. Furthermore, the function summarizes the results with tables and graphs providing a well-ordered data structure and a plot function. The package together with CoxBenchmarking is available at https://github.com/joseTamezPena/FRESA.CAD