Valeria Gonzalez on AI’s Role in Healthcare Innovation

In this episode of the Kanawha Valley Hustlers podcast, I talk with Valeria Gonzalez about her work in artificial intelligence and machine learning in healthcare. Valeria shares that she is currently focusing on implementing predictive algorithms in emergency rooms, though she faces challenges in finding the right use cases and gaining acceptance for new technology.

She explains that some ER nurses are resistant to AI, fearing it cannot replicate the human touch required for patient care. Others see it as a necessary step forward. Valeria emphasizes that AI is a tool meant to support, not replace, healthcare workers, especially since data sharing between hospitals is limited, making it impossible for AI to fully take over tasks at this time.

Valeria’s journey into the field began with her bachelor’s degree in marketing and later a master’s in data and information science. Her work at the College of Science introduced her to machine learning applications in DNA research, particularly studies on why COVID-19 disproportionately impacted Hispanic populations. This path led her to the healthcare sector, where she saw opportunities to make a difference.

When I ask her to break down machine learning, she describes it as a subset of AI. Neural networks are at the core, processing vast amounts of data to improve predictions and outcomes. She uses diagrams to illustrate how these networks fit within the broader context of AI.

We discuss how this technology is being applied to various fields, with Valeria focusing on predictive AI rather than generative AI, such as tools like ChatGPT or image generators. Predictive AI uses past patterns to anticipate future outcomes, such as identifying cancerous moles or analyzing patient histories to flag potential health risks.

Valeria explains that predictive AI can save time and resources by processing data from thousands of patients simultaneously, offering insights that enhance, rather than replace, human decision-making. She concludes by emphasizing that AI is efficient and fast but still requires collaboration with healthcare professionals to achieve its full potential.

This conversation highlights the evolving role of AI in healthcare and the importance of bridging the gap between technology and human expertise.

Leave a Reply

Your email address will not be published. Required fields are marked *