construction of deep learning models for the analysis of nuclear pleomorphism in breast cancer, as well as improvement of nucleus detection algorithms. Data collection and preprocessing Evaluation of the models and algorithms Collaboration with the research team

Contribution to scientific progress, Validation and comparison with existing methods, Construction of accurate models A preprocessing step towards improving nuclei segmentation methods. Journal of Pathology Informatics, page 100315, 2023

Review and evaluation of the simulation models and algorithms used to guarantee their validity and reliability. Supervision of data collection and its correct incorporation. Analysis of the results obtained and verification of their consistency with the project objectives. Detailed technical reports summarizing the findings and providing recommendations to improve the quality of the simulation and modeling products. Collaboration with the development team

raise the bar for quality and reliability of simulation and modeling products

identify the required functionalities, establish the appropriate data structure and define the user interface for each module. produce detailed technical documentation that describes the architecture, design and functionality of each module.{ ***}Collaboration with the development team Testing and validation

An adequate data structure was established and interfaces were defined to facilitate the interaction and exchange of information between the different components of the clinical record system.