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SUMMARY:AI in Med Lecture: Dr. Anne Martel
DESCRIPTION:SBME x BMIAI x the BC Translational Digital Pathology Initiative are proud to co-present a special lecture:\n“Artificial Intelligence and digital pathology: dealing with the annotation bottleneck”\nABSTRACT \nThe introduction of scanners that are capable of digitizing microscopic slides at high magnification has led to an explosion of interest in computational pathology in general and deep learning applied to whole slide images (WSIs) in particular. In my lab at Sunnybrook\, we are developing AI models that can detect cancer\, automatically segment regions of interest\, and learn predictive and prognostic models that can be used to guide treatment decisions. In this talk I will outline some of the unique challenges of working with these extremely large WSIs and discuss some of the approaches that we have developed to overcome the problems of sparse annotations and weak\, noisy labels\, including self-supervision and multiple instance learning. I will also outline some of the challenges in deploying AI algorithms to the clinic.
URL:https://scienceinvancouver.com/event/ai-in-med-lecture-dr-anne-martel/
LOCATION:Online
ATTACH;FMTTYPE=image/jpeg:https://scienceinvancouver.com/wp-content/uploads/sites/1/2021/12/Seminar-Poster-2022.01.20-Anne-Martel-Med-in-AI-2048x1152-1.jpg
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CREATED:20211217T202505Z
LAST-MODIFIED:20211217T202505Z
UID:26484-1642676400-1642680000@scienceinvancouver.com
SUMMARY:AI in Med Lecture: Dr. Anne Martel
DESCRIPTION:SBME x BMIAI x the BC Translational Digital Pathology Initiative are proud to co-present a special lecture:\n“Artificial Intelligence and digital pathology: dealing with the annotation bottleneck”\nABSTRACT \nThe introduction of scanners that are capable of digitizing microscopic slides at high magnification has led to an explosion of interest in computational pathology in general and deep learning applied to whole slide images (WSIs) in particular. In my lab at Sunnybrook\, we are developing AI models that can detect cancer\, automatically segment regions of interest\, and learn predictive and prognostic models that can be used to guide treatment decisions. In this talk I will outline some of the unique challenges of working with these extremely large WSIs and discuss some of the approaches that we have developed to overcome the problems of sparse annotations and weak\, noisy labels\, including self-supervision and multiple instance learning. I will also outline some of the challenges in deploying AI algorithms to the clinic.
URL:https://scienceinvancouver.com/event/ai-in-med-lecture-dr-anne-martel-2/
LOCATION:Online
ATTACH;FMTTYPE=image/jpeg:https://scienceinvancouver.com/wp-content/uploads/sites/1/2021/12/Seminar-Poster-2022.01.20-Anne-Martel-Med-in-AI-2048x1152-1.jpg
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DTEND;TZID=America/Vancouver:20220120T120000
DTSTAMP:20260617T002920
CREATED:20211217T202505Z
LAST-MODIFIED:20211217T202505Z
UID:28099-1642676400-1642680000@scienceinvancouver.com
SUMMARY:AI in Med Lecture: Dr. Anne Martel
DESCRIPTION:SBME x BMIAI x the BC Translational Digital Pathology Initiative are proud to co-present a special lecture:\n“Artificial Intelligence and digital pathology: dealing with the annotation bottleneck”\nABSTRACT \nThe introduction of scanners that are capable of digitizing microscopic slides at high magnification has led to an explosion of interest in computational pathology in general and deep learning applied to whole slide images (WSIs) in particular. In my lab at Sunnybrook\, we are developing AI models that can detect cancer\, automatically segment regions of interest\, and learn predictive and prognostic models that can be used to guide treatment decisions. In this talk I will outline some of the unique challenges of working with these extremely large WSIs and discuss some of the approaches that we have developed to overcome the problems of sparse annotations and weak\, noisy labels\, including self-supervision and multiple instance learning. I will also outline some of the challenges in deploying AI algorithms to the clinic.
URL:https://scienceinvancouver.com/event/ai-in-med-lecture-dr-anne-martel-3/
LOCATION:Online
ATTACH;FMTTYPE=image/jpeg:https://scienceinvancouver.com/wp-content/uploads/sites/1/2021/12/Seminar-Poster-2022.01.20-Anne-Martel-Med-in-AI-2048x1152-1.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20220120T110000
DTEND;TZID=America/Vancouver:20220120T120000
DTSTAMP:20260617T002920
CREATED:20211217T202505Z
LAST-MODIFIED:20211217T202505Z
UID:31182-1642676400-1642680000@scienceinvancouver.com
SUMMARY:AI in Med Lecture: Dr. Anne Martel
DESCRIPTION:SBME x BMIAI x the BC Translational Digital Pathology Initiative are proud to co-present a special lecture:\n“Artificial Intelligence and digital pathology: dealing with the annotation bottleneck”\nABSTRACT \nThe introduction of scanners that are capable of digitizing microscopic slides at high magnification has led to an explosion of interest in computational pathology in general and deep learning applied to whole slide images (WSIs) in particular. In my lab at Sunnybrook\, we are developing AI models that can detect cancer\, automatically segment regions of interest\, and learn predictive and prognostic models that can be used to guide treatment decisions. In this talk I will outline some of the unique challenges of working with these extremely large WSIs and discuss some of the approaches that we have developed to overcome the problems of sparse annotations and weak\, noisy labels\, including self-supervision and multiple instance learning. I will also outline some of the challenges in deploying AI algorithms to the clinic.
URL:https://scienceinvancouver.com/event/ai-in-med-lecture-dr-anne-martel-4/
LOCATION:Online
ATTACH;FMTTYPE=image/jpeg:https://scienceinvancouver.com/wp-content/uploads/sites/1/2021/12/Seminar-Poster-2022.01.20-Anne-Martel-Med-in-AI-2048x1152-1.jpg
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DTSTART;TZID=America/Vancouver:20220120T110000
DTEND;TZID=America/Vancouver:20220120T120000
DTSTAMP:20260617T002920
CREATED:20211217T202505Z
LAST-MODIFIED:20211217T202505Z
UID:32642-1642676400-1642680000@scienceinvancouver.com
SUMMARY:AI in Med Lecture: Dr. Anne Martel
DESCRIPTION:SBME x BMIAI x the BC Translational Digital Pathology Initiative are proud to co-present a special lecture:\n“Artificial Intelligence and digital pathology: dealing with the annotation bottleneck”\nABSTRACT \nThe introduction of scanners that are capable of digitizing microscopic slides at high magnification has led to an explosion of interest in computational pathology in general and deep learning applied to whole slide images (WSIs) in particular. In my lab at Sunnybrook\, we are developing AI models that can detect cancer\, automatically segment regions of interest\, and learn predictive and prognostic models that can be used to guide treatment decisions. In this talk I will outline some of the unique challenges of working with these extremely large WSIs and discuss some of the approaches that we have developed to overcome the problems of sparse annotations and weak\, noisy labels\, including self-supervision and multiple instance learning. I will also outline some of the challenges in deploying AI algorithms to the clinic.
URL:https://scienceinvancouver.com/event/ai-in-med-lecture-dr-anne-martel-5/
LOCATION:Online
ATTACH;FMTTYPE=image/jpeg:https://scienceinvancouver.com/wp-content/uploads/sites/1/2021/12/Seminar-Poster-2022.01.20-Anne-Martel-Med-in-AI-2048x1152-1.jpg
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