Roque Lopez

BDI-Kit, a Python toolkit specifically designed to streamline biomedical data integration. BDI-Kit provides a suite of methods and intuitive APIs to facilitate the efficient harmonization of diverse datasets. By simplifying the integration process, BDI-Kit enables practitioners and researchers to create unified datasets.

This is part of the BDF project of ARPA-H.

AlphaD3M, an AutoML library implemented in Python that automatically synthesizes end-to-end pipelines for different machine learning tasks and different data types. Through an API, it allows the users to explore the input data and the derived pipelines, as well as customized the pipelines.

This tool is part of NYU’s implementation of the Data Driven Discovery project (D3M), DARPA.

Monograph title: Automatic Aspect-Based Opinion Summarization Methods

In this master’s project are presented investigations to generate extractive and abstractive summaries of opinions using an aspect-based approach. Besides using known methods in the area, it also was proposed two new methods for Portuguese language which got the best performance in the experiments.

Monograph title: Medical Documents Classification based on Keywords using Semantic Information

In this monograph, it is presented a method to classify medical documents which improves the results of Naive Bayes and Rocchio algorithm. This method, in addition to considering statistical information, taking into account the semantic relatedness between the keywords of medical documents.