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© 2026 Denis Jacob Machado. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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The notes in here are associated with a book project and both are a work in progress that may contain many errors as none have underwent final review. None of the pages or chapters have been finalized at this time. Use these materials with caution.
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Contemporary debate on the problems and potential scientific advancements in the utilization of artificial intelligence approaches, including supervised and unsupervised machine learning, deep learning, generative models, Bayesian networks, and AI-guided probabilistic inference, large-scale language models, and hybrid and AutoML models.
Contemporary Debates on Artificial Intelligence in Biomedical Science
AI in Phylogenetics, Bioinformatics & Biomedical Sciences — FAQ
Application of probabilistic inference methods for phylogenomic reconstruction, considering theoretical aspects, possibility of full implementation, computational and technical capacity, and limitations in interpreting results.
A classification of maximum likelihood methods in phylogenetics
In the real world, priors always matter
Theoretical-philosophical foundation on the concepts of character, homology, and homoplasy, as well as the implementation of these concepts in contemporary phylogenetic reconstruction strategies based on high-performance sequencing.