Past Events

MaLMIC sponsored machine learning sessions at ImNO 2024 – Symposium Session March 2024

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MaLMIC is pleased to support the ImNO 2024 symposium in Mississauga ON on March 19 and 20, 2024. Here are some of the sessions featuring AI and machine learning:
– Keynote: Anne Martel will talk about AI for medical image analysis: Living with limited data
– Debate: The role of AI in medicine
– Panel: Commercialization of AI-enabled medical imaging technology
Throughout the symposium, there will also be talks, pitches and posters on AI, deep learning and machine learning.
We hope you can join us at ImNO 2024!

Computational pathology and cancer prediction – Forum, January 19th, 2024

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This forum will focus on computational pathology for outcome prediction in cancer. Mattias Rantalainen will be the first speaker talking about his research program and the work of Stratipath predictive models that are being translated into the clinic. Faisal Mahmood, will be the second speaker talking about the work in his lab that uses machine learning, data fusion and medical image analysis to develop streamlined workflows for objective diagnosis, prognosis, and biomarker discovery. The presentations will be followed by questions and answers about the talks, and discussion focused on lessons learned, opportunities to collaborate, and sharing of data.

Translating AI/ML into products – Forum, November 24, 2023

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This forum will focus on translating AI-based innovations in medicine into the commercial world and the clinic. The first speaker, Qian Cao, will talk about developing AI-enabled software as a medical device and the FDA Centre for Devices and Radiological Health’s perspective on AI/ML devices. Our second speaker, Eli Gibson, will talk about the complexities of translating AI/ML ideas from a manufacturer’s perspective and showcase examples. The presentations will be followed by questions and answers about the talks, and discussion focused on lessons learned, opportunities to collaborate, and sharing of data.

Machine Learning to Predict Disease Progression – Forum, October 20, 2023

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The October forum will focus on using machine learning to predict disease progression. Su-In Lee, will describe the use of text and phenotypic data in medical records for predicting patients’ clinical course, and potential uses for medical management. The presentation will be followed by questions and answers about the talk, and discussion focused on lessons learned, opportunities to collaborate, and sharing of data.

Ontario Tumour Bank and Ontario Health Study: Machine learning resources and projects – Forum, September 29, 2023

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The MaLMIC fall forum, hosted by Dr. Lincoln Stein, will focus on human sample and data resources for machine learning research. Dr. Dianne Chadwick will describe the Ontario Tumour Bank (OTB)’s repository of human cancer biospecimens and de-identified clinical data. Following this, Dr. Philip Awadalla will provide an overview of the Ontario Health Study (OHS) and describe research from his lab using simulation-based and machine learning tools to analyze evolution in non-recombining systems and the use of liquid biopsies to identify genetic and epigenetic markers indicative of cancer development. The presentations will be followed by questions and answers about the talks, and discussion focused on lessons learned, opportunities to collaborate, and the availability of data and biosamples from OTB and the OHS.

Med-ImageNet: Creation of a Compendium of AI-Ready Medical Imaging Data for Deep Learning Analysis – Forum, July 21, 2023

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Artificial Intelligence (AI) applied to medical images has the potential to transform patient care, especially in radiation oncology where radiological imaging is ubiquitous and treatment planning is time consuming.
AI models are data hungry but medical data are often insufficient for many applications. Building foundational models and fine-tuning them for specific medical tasks with only a few data points represents a new avenue of research with high translational potential. However, there is a lack of large compendia of radiological data that are sufficiently curated for building these foundational models.
In this session, the presenters will describe current work on implementing Med-ImageNet, a compendium of radiological images that have been standardised to develop deep learning models, such radiomics predictors or the foundational MedSAM model.

Machine Learning in Computational Neuroimaging- Forum, June 23, 2023

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Enforcing geometry in machine learning for computational neuroimaging
The June forum centers on the vital role of geometric principles in machine learning applications for medical imaging. The first presentation by Ali Khan will address machine learning applications in computational neuroimaging, exploring how geometry can inform the representation of neuroanatomy. The second presentation by Uzair Hussain will explore geometric machine learning in computational diffusion MRI, describing a novel approach for performing machine learning on data modelled as a sphere. The talks will be followed by discussion focused on lessons learned, opportunities to collaborate, and sharing of resources.

Machine Learning in Computational Pathology- Forum, May 26, 2023

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For the May forum on machine learning in computational pathology, the first presentation by April Khademi, a researcher, will be about the past, present and future of digital pathology and AI. The second presentation by Phedias Diamandis, a pathologist, will be about approaches to solve implementation challenges of AI in the real world. The talks will be followed by discussion focused on lessons learned, opportunities to collaborate, and sharing of resources.

Machine Learning and Precision Health – Forum, April 21, 2023

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For the April forum on machine learning in precision health, the first presentation by Ross Mitchell, a Professor of Medicine and AI scientist at the University of Alberta, will be about AI and Precision Health. The second presentation by Jacob Jaremko a radiologist, entrepreneur and AI scientist, will be about AI augmented ultrasound imaging. The talks will be followed by discussion focused on lessons learned, opportunities to collaborate, and sharing of resources.

MaLMIC sponsored machine learning session at ImNO 2023 – Symposium Session, March 23/24, 2023

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MaLMIC is pleased to support three sessions at the ImNO 2023 symposium in London ON on Friday, March 24