LEAP MedTech Club Coming!
“Connecting great minds. Inspiring medtech innovations.” - LEAP MedTech
In the past two months, LEAP together with MIT CEO has successfully hosted 8 sessions in BootCamp II, covering many different aspects in entrepreneurship in biotech and medtech, including general sessions on business, finance, legal, etc and focused sessions on the hot topics in biotech and medtech. We received many positive feedback in medtech and healthcare in particular, which motivates us to continue to provide opportunities for LEAPers to come together, discuss and share their thoughts in medtech innovations, applications and beyond.
Intro to MedTech Club
MedTech Club will be our dedicated platform for sharing topics and collaborating in the area of medtech and healthcare in general and connecting the individuals who are interested. We will host events occasionally either online or offline, and we hope more people could join us!
If you have topics you are interested to discuss, or practical experience or research innovations to share, we would love to hear from you! We are still shaping in progress and exploring different event forms, hoping to promote the vibes of innovation and connection.
On 05/14 Friday this week, we will host the first event in MedTech Club online through Zoom! We invited Yun Liu, PhD, Staff Research Scientist at Google Health to share their research achievements on Deep Learning for Medical Imaging.
There has been intense interest in deep learning for medical imaging, primarily for diagnostic applications. In this talk I will provide a brief survey of two types of applications at Google Health. The first type of work involves using deep learning to replicate diagnostic tasks that doctors perform using the same images, such as detecting diabetic and non-diabetic eye diseases from photographs of the back of the eye, and detecting metastatic cancer for breast cancer in histopathology images. I will further show how these models can be integrated into tools that doctors can use. The second type of work involves using deep learning to extract novel insights from medical images, and has the potential to make new discoveries about human physiology and disease that we did not previously appreciate. In this category, I will cover three applications: diabetic macular edema, cardiovascular risk factors, and anemia.
Everyone is welcome!
To register, follow the link: