David Palazon Palau

Conducted advanced data analysis tasks for managing complex chronic patients (PCC), including the development of predictive models to identify hospital readmission risks and the evaluation of healthcare intervention effectiveness. Implemented data-driven strategies to optimize clinical resources and support decision-making, aiming to enhance healthcare quality and efficiency in the treatment of these patients.

• ETL processes to structure and clean the tabular data provided by the hospital.
• Exploratory Data Analysis (EDA) to identify patterns and trends.
• Development of geolocation maps for data visualization.
• Implementation of Survival Analysis models to study the time between hospital admissions for patients.

Development of Innovative Methods for Early Glaucoma Diagnosis Using Machine Learning

• Achieved models with 85% (±5%) recall and 78% precision in detecting positive glaucoma cases.
• Published results at the CASEIB conference, contributing to advancements in this field.