During the talks at the Nexus Informatics conference of 2022, I took a peek at various website and articles. These were either ones that the speakers mentioned or ones I googled on a topic that they covered. I am placing links to these here in case I want to look at them later.
Bidirectional Encoder Representations from Transformers (BERT)
Wikipedia. BERT (language module). Available in [html format][wiki1].
- An encoding system that replaces words with a numeric vector that helps to identify closely related terms in text mining or natural language processing.
Bootstrap Enhanced Penalized Regression
Samantha V. Abram, Nathaniel E. Helwig, Craig A. Moodie, Colin G. DeYoung, Angus W. MacDonald III, Niels G. Waller. Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data. Frontiers in Neuroscience, 2016-07-28. DOI: 10.3389/fnins.2016.00344. Available in html format.
- Neuroimaging creates massive data files. This paper offers one approach for handling this type of data.
Few-Shot Learning
Dhanya Thailappan. An Introduction to Few-Shot Learning. Analytics Vidhya blog, 2021-05-01. Available in html format
- Few-Shot learning is an alternative to supervised learning when the number of training samples is small.
Iterative Random Forests
Sumantu Basu. iterative Random Forests (iRF). Available in a github repository.
- An interesting enhancement to the popular Random Forests technique that does a better job at feature selection.
Nonlinear longitudinal data
Ahmed Elhakeem, Rachel A. Hughes, Kate Tilling, Diana L. Cousminer, Stefan A. Jackowski, Tim J. Cole, Alex S. F. Kwong, Zheyuan Li, Struan F. A. Grant, Adam D. G. Baxter-Jones, Babette S. Zemel, Deborah A. Lawlor. Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies. BMC Medical Research Methodology, 2022-03-15, 22(68). DOI: 10.1186/s12874-022-01542-8.
- A nice overview to different approaches to summarizing nonlinear fits to longitudinal models.
Pathway Analysis
Elisa Cirillo, Laurence D. Parnell, Chris T. Evelo. A Review of Pathway-Based Analysis Tools That Visualize Genetic Variants. Frontiers in Genetics, 2017-11-07, 8(174). DOI: 10.3389/fgene.2017.00174. Available in html format.
- A nice overview of the various software packages that help visualize genetic variants using pathways.
Recursive Feature Elimination
Jason Brownlee. Recursive Feature Elimination (RFE) for Feature Selection in Python. Machine Learning Mastery blog, 2020-05-25. Available in html format.
- This page covers RFE using the scikit-learn library in Python.
An earlier version of this page was published on new.pmean.com.