tinyML Talks: Unleashing The Power of Tiny Neural Network Models in Medical Devices

In today’s rapidly evolving healthcare landscape, the integration of machine learning technology is driving fundamental transformations. Picture a future where wearable devices become indispensable allies, offering unprecedented precision in diagnosing medical conditions. This presentation delves deep into the realm of advanced and efficient neural network models, particularly tinyML, and their pivotal role in reshaping the future of medical diagnosis through long-term monitoring. Furthermore, personalization emerges as a crucial need that impacts the need and use around the medical devices design and technology. Continuously evolving and innovative models are refining on-edge performances, thereby enhancing the potential of the next generation of these devices. During this session, we will explore some of the novel and compatible tinyML models that have shown promising potential, discussing their implications and contributions to the future.

Date

May 14, 2024

Location

Virtual

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Discussion

Schedule

Timezone: PST

Unleashing The Power of Tiny Neural Network Models in Medical Devices

Zhaojing (Jim) HUANG, PhD Candidate at the School of Biomedical Engineering

University of Sydney

Leping (Steve) YU, MPhil candidate

University of Sydney's School of Biomedical Engineering

Zhaojing (Jim) HUANG, PhD Candidate at the School of Biomedical Engineering

University of Sydney

In today’s rapidly evolving healthcare landscape, the integration of machine learning technology is driving fundamental transformations. Picture a future where wearable devices become indispensable allies, offering unprecedented precision in diagnosing medical conditions. This presentation delves deep into the realm of advanced and efficient neural network models, particularly tinyML, and their pivotal role in reshaping the future of medical diagnosis through long-term monitoring. Furthermore, personalization emerges as a crucial need that impacts the need and use around the medical devices design and technology. Continuously evolving and innovative models are refining on-edge performances, thereby enhancing the potential of the next generation of these devices. During this session, we will explore some of the novel and compatible tinyML models that have shown promising potential, discussing their implications and contributions to the future.

Leping (Steve) YU, MPhil candidate

University of Sydney's School of Biomedical Engineering

Leping Yu, a second-year Master’s student at the University of Sydney’s School of Biomedical Engineering, is dedicated to researching circuit design, signal processing, and system development, particularly in the realm of EEG hardware, showcasing a strong interest in exploring diverse devices for EEG measurements.

Schedule subject to change without notice.