Track: Keynote VoiceTech |
| Training Machine Learning Classification Models for Creating Real-Time Data Points of Medical Conditions |
| As machine learning (ML) continues to revolutionize medical diagnostics, this field explores the transformative potential of leveraging AI technologies to assist healthcare professionals in creating tools for collecting data points leading to recognizing medical conditions, such as Parkinson's Disease. Through a collaborative presentation blending expertise in data science and human movement analysis, we will discuss methodologies and insights crucial to training machine learning models. This session will explore the underpinnings of image, video, and audio recognition techniques for multi-modal applications. Our focus will be on the practical implications for healthcare, emphasizing the integration of AI into clinical workflows to enhance diagnostic accuracy and efficiency. As the world moves further into the digital space, areas like telehealth must embrace advancements and tools to assist medical professionals. This discussion will bridge the gap between theory and practice, demonstrating the future possibilities of AI in improving patient care. Expect live demonstrations showcasing applications of ML models in clinical scenarios. Attendees will leave equipped with actionable insights and access to comprehensive code resources, empowering them to implement recognition solutions in their own domains, subjects, and areas of interest. |
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| Presentation Video |
| Presentation Notes |
| Alkema-vonThenen-Training_Machine_Learning_Classification_Models_for_Creating_Real_Time_Data_Points_of_Medical_Conditions1.pdf |
Real Time Communications Conference & Expo at Illinois Tech
IEEE International Conference
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