Real-Time Disease and COVID-19 Detection Pipeline from Voice for Performance Sports

Voice-based disease detection with Artificial Intelligence has the potential to revolutionize healthcare, offering cost-effective, non-invasive, and accessible diagnostic methods for a wide range of diseases. The development of voice-based disease detection systems requires collaboration between multiple fields, including data science, linguistics, machine learning, and medical research. This interdisciplinary approach has led to the creation of innovative solutions that advance both healthcare and technology. By incorporating individual patient data, AI-driven voice diagnostics can provide personalized insights into a person's health, enabling tailored treatment plans that better address individual needs. The goal of the study was to find a feasible, machine learning-supported pipeline, by combining the feature extraction methods to support professional sports staff to predict disease from voice sample and prevent cross contamination in joint events.