Resolución de Problemas Combinatorios Jobs

Managed a targeted claims recovery project focused on resolving denials rooted in CPT coding errors, mismatched diagnosis codes, and payer-specific coding compliance issues for a US-based medical practice. Coding-related denials represent one of the most common and preventable sources of revenue loss in any practice, and this engagement addressed that problem systematically. The project involved identifying denied and rejected claims where the primary denial reason was linked to incorrect or unsupported CPT codes, ICD-10 diagnosis mismatches, unbundling issues, or missing modifiers. Each claim was reviewed against payer-specific coding guidelines and CMS standards to determine the appropriate correction pathway — whether resubmission, appeal, or clinical documentation improvement. Cl...

I have already trained and deployed a Logistic Regression model in Streamlit that classifies breast-tumour samples as malignant or benign. What I need now is a polished data-visualization layer so users can quickly grasp how each feature influences the prediction. My immediate focus is on bar-chart visualisations. I want clear, well-labelled bars that compare malignant vs. benign distributions, show feature importances, and surface any other insight you think adds value. The work should plug straight into my current Streamlit app and read from the same Pandas DataFrame I am already passing to the model. Although the main task is visualisation, I am also experimenting with feature selection, so if your code can be structured in a way that makes it easy to toggle feature subsets, that wi...