Lab to Tech: Brain Insights from Neuroimaging; AI-augmented Ultrasound Reporting

We're excited to announce our first meet-up event of 2024. This time we will explore the diverse landscape of AI applications in medical imaging, from groundbreaking multidisciplinary research to crafting innovative tech solutions for clinical deployment. Join us for an evening of knowledge sharing, featuring perspectives from both academia and industry, along with networking opportunities. Complimentary refreshments will be provided. We look forward to seeing you there.

TALK DETAILS
Reimagining Breast & Thyroid Ultrasound with AI (Milad Mohammadzadeh)
Speaker Bio: Milad is a co-founder and director of See-Mode, a medtech startup based in Melbourne leveraging AI to assist clinicians in increasing the efficiency and quality of reporting on medical images. Milad's coming from a Mechanical Engineering and Physics background, and prior to founding See-Mode, he worked on biomedical fluid dynamics and minimally invasive surgery techniques for his PhD.
Talk Outline
In this presentation, Milad will lead us through See-Mode's journey, discussing current challenges in thyroid ultrasound and how See-Mode uses AI to simplify the workflow. The talk will then delve into the engineering challenges faced, the solutions devised to overcome those obstacles, and provide insights into See-Mode's deployment in clinical practice.

Combining Time-series Analysis and Machine Learning to Understand Brain Function in Health and Disease (Annie Bryant)
Speaker Bio
Annie is a third-year PhD candidate at The University of Sydney, with her thesis focusing on measuring nuanced changes in brain-wide dynamics across diverse neurological disorders. Originally from New Jersey, Annie spent several years in Boston working in neurodegenerative disease research between Massachusetts General Hospital and Merck Research Laboratories. After completing her studies in neuroscience and bioinformatics, Annie moved to Sydney to connect with global leaders in quantitative neuroimaging and brain dynamics, where she maintains a keen interest in understanding how the accumulation of pathological proteins in Alzheimer’s disease modulates brain activity at multiple scales.
Talk Outline
Modern neuroimaging provides a plethora of data at our fingertips -- how can we best apply methods from machine learning to uncover salient and translationally relevant insights from this data? This question reverberates throughout neuroscience at multiple scales, from individual neuron firing dynamics to large-scale brain network activity. The recent development of open-source libraries of comprehensive and interdisciplinary time-series features allows us to thoroughly survey diverse properties of brain activity, which can be combined with machine learning classifiers to infer differences across traits or conditions. This talk will explore the use of feature-based time-series analysis and machine learning techniques applied to functional neuroimaging data to reveal whole-brain dynamics signatures across disorders, with a particular focus on mild cognitive impairment and Alzheimer's disease.

TIMELINE
5:30 - 6:00: Arrival and networking
6:00 - 6:30: Reimagining Breast & Thyroid Ultrasound with AI (Milad Mohammadzadeh)
6:30 - 7:00: Combining Time-series Analysis and Machine Learning to Understand Brain Function in Health and Disease (Annie Bryant)
7:00 - 7:30 - More networking

VENUE
Healius head office
Liberty Place, Level 22/161 Castlereagh St, Sydney NSW