Small clinical tabular datasets require interpretable machine learning because deep learning is often impractical and ensemble models can be difficult to inspect. A key pitfall is that statistical significance does not necessarily imply predictive utility. Using data from the Panama Aging Research Initiative--Health Di...
Antony García, Gabrielle B. Britton, Alcibiades E. Villarreal et al.· 0 citations
Falls in older adults are often preceded by changes in mobility, balance, and postural transitions. This paper presents a wireless smart insole platform and machine-learning workflow for recognizing sitting, standing, walking, and unstable walking from plantar-pressure and inertial signals. Each insole integrates 16 ac...
E. Rios, Antony García, Feng-Pei Yuan et al.· 0 citations
Black-box models limit the adoption of artificial intelligence in medicine due to their lack of interpretability and reproducibility. We introduce a statistically grounded framework that provides fully interpretable, rule-based clinical classification using the Bernoulli Na\"ive Bayes (BNB) model. The method applies su...
Antony García, A. Noriega, Gabrielle Britton et al.· arXiv.org· 0 citations
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