Classical Machine Learning for Infant Medical Diagnosis with Charles Onu - TWiML Talk #112

This article discusses the application of classical machine learning techniques, specifically Support Vector Machines (SVMs), to diagnose infant asphyxia. The focus is on the work of Charles Onu and his startup, Ubenwa, which uses audio analysis of infant cries to detect the condition. The article highlights the data collection process, challenges in platform deployment, and the potential impact of this technology on reducing infant mortality. It also promotes the TWiML podcast and an upcoming AI conference, suggesting a broader interest in AI's role in various fields. The use of classical machine learning is noteworthy, as it contrasts with the current trend towards deep learning.