Simply put, bioinformatics is the study of biology using computers. Computational biology, clinical informatics, and even systems biology all share a similarly in this definition, with nuanced differences defined by the communities of practice using the term(s). Often these terms are used synonymously, and sometimes they are used with great precision within communities of practice. For these reasons, it is necessary to levelset on a definition.
For machine learning discussion in these articles, bioinformatics is used broadly, but with a focus more on the molecular biology side of informatics to include gene expression and DNA analysis.
Broadly speaking, here is a little more context on how these terms are often distinguished in the practice of computer modeling and machine learning: Clinical informatics, as compared with bioinformatics, tends to also look at molecular biology assays, but with a greater focus on the electronic health records (EHR). Computational biology focuses more on the proteomics, post-translational modifications, and drug interactions side of analysis than does the bioinformatician, who concerns themself more with sequencing pipelines and predictive analytics on genetic and transcriptomic function. Systems biology focuses more on the metabolomic side of the equation, concerning themselves more with pathways and their products.