Research project for automating systematic literature reviews. Best Paper Award of WEBIST 2022

ML-SLRC

S2query is a library to search papers from Semantic Scholar.

S2Query

quarto-actions

Resumo sobre o comportamento de RNN do básico a aplicações básicas sobre sua funcionalidade.

EvalAI-Starters

ARL_trab

Repositório da disciplina ce089 - Estatística Computacional II

ce089

A collection of fully labeled systematic review datasets (title-abstract screening)

systematic-review-datasets

We employed pre-trained BERT models (distillBERT, BioBert, and SciBert) for text-classifications of  the titles and abstracts of clinical trials in medical psychology. The average score of AUC is 0.92. A stacked model was then built by featuring the probability predicted by distillBERT and keywords of search domains. The AUC improved to 0.96 with F1, precision, and recall increasing to 0.95, 0.94, and 0.96 respectively. Training sample size of 100 results in the most cost-effective performance. 

ML-SLRC

Jupyter Notebook, Python

09/01/23

Research project for automating systematic literature reviews. Best Paper Award of WEBIST 2022

Jupyter Notebook, Python

09/01/23

ML-SLRC

Research project for automating systematic literature reviews. Best Paper Award of WEBIST 2022

Python

09/01/23

S2Query

S2query is a library to search papers from Semantic Scholar.

Jupyter Notebook

16/08/22

RNN

Resumo sobre o comportamento de RNN do básico a aplicações básicas sobre sua funcionalidade.