By Dr. Juan Barrios
In the early days of modern medicine, the promise of more personalized and preventive care seemed distant on the horizon. However, with the advent and maturation of technology and artificial intelligence (AI), that future is now within reach. It’s in this medical-technological landscape that the battle against breast cancer, the second leading cause of death in Costa Rica, with an incidence rate of 43 per 100,000 women, becomes more optimistic.
We have the development and technological innovation of clinical informatics, with the ability to analyze vast amounts of data, along with increasingly precise algorithms, changing not only how we diagnose but also how we prevent and treat this disease. Let’s explore how various technologies and algorithms are redefining this field.
- Convolutional Neural Networks (CNN) in Computer Vision: CNNs, through multiple layers of filtering, can identify and learn features in images with high precision. In the context of mammograms, early detection of anomalies is essential, and CNNs have proven to be powerful tools, significantly reducing the rates of misdiagnosis.
- Genomic Sequencing and Bioinformatics Algorithms: With algorithms like Genome-Wide Association Studies (GWAS), it’s feasible to identify genetic variants that increase the risk of breast cancer. These findings, such as BRCA1 and BRCA2 mutations, offer opportunities for specific preventive interventions.
- Genetic Algorithms in Treatment Optimization: Inspired by evolutionary theory, genetic algorithms seek optimal solutions through selection, crossover, and mutation mechanisms. In breast cancer treatment, they can be used to personalize therapeutic regimens, optimizing factors such as dosage and drug combinations to maximize effectiveness and minimize side effects. These types of algorithms are widely used in process optimization in healthcare services.
- Electronic Health Record Systems and Machine Learning: These records, powered by advanced machine learning techniques, can predict risks and anticipate diagnoses. Algorithms like clustering or k-means segment patients by risk, allowing for personalized interventions and follow-ups.
- Augmented Reality (AR) and Surgical Procedures: The combination of AR with advanced imaging technologies allows surgeons to have a real-time three-dimensional view of the area being treated, resulting in more precise and less invasive procedures.
- Prevention Through Predictive Analysis: Prevention is the most powerful weapon against any disease, and with the use of tools like decision trees and random forests, we analyze data to predict the probability of breast cancer occurrence, guiding preventive strategies.
The convergence of advanced technology and medicine is transforming the fight against breast cancer. These advances not only promise more accurate diagnoses but also more effective treatments and, most importantly, powerful prevention strategies. The future of medicine is here, and it’s technologically more promising every day.
This article was written by Dr. Juan Ignacio Barrios, a medical doctor and specialist in medical informatics. Dr. Barrios has studied Business Intelligence, Big Data, and Data Science, as well as Artificial Intelligence in the medical field. He collaborates with the clinical informatics department at the University of Barcelona.