Miscellaneous

[Airicist]

Math can help uncover cancer's secrets | Irina Kareva

Published on Apr 24, 2018

Irina Kareva translates biology into mathematics and vice versa. She writes mathematical models that describe the dynamics of cancer, with the goal of developing new drugs that target tumors. "The power and beauty of mathematical modeling lies in the fact that it makes you formalize, in a very rigorous way, what we think we know," Kareva says. "It can help guide us to where we should keep looking, and where there may be a dead end." It all comes down to asking the right question and translating it to the right equation, and back.

[Airicist]

Google researchers are uysing AR microscopes to detect cancer

Published on May 1, 2018

The special AR microscopes (ARM) use machine learning to detect cancerous cells. Doctors are able to monitor these microscopes nearby, cutting down their work time. This technology could be used to detect tuberculosis and malaria in the future.

[Airicist]

What is Cancer? | The Cancer Series

Published on May 2, 2018

Let's start at the beginning. Cancer can be scary, but before we learn about how we're using science to treat and beat this disease, we'll cover what it is and how it works in this first video of The Cancer Series

[Airicist]

Fighting Cancer With Immunotherapy - Prof. Cyrille J. Cohen

Published on Jun 7, 2018

Fighting Cancer with an Artificially Enhanced Immune System
Prof. Cyrille J. Cohen, Bar-Ilan University

[Airicist]

This chain-smoking robot is taking one for the team

Published on Jun 13, 2018

Researchers at the WYSS Institute at Harvard University developed a robot whose only task is smoking cigarettes. The smoke then goes through a tiny chip, lined with living human cells, that is used to study the effects of smoking on our lungs.

[Airicist]

Interview with Dr Kinkel, Switzerland, about her experience with AI Breast

Published on Jun 27, 2018

-Through this interview, Dr Kinkel presents her background, her current practice activities and tells her experience with AI Breast. Key highlights:
-Productivity improvement with auto-annotation feature on breast with multi-lesions
-Confidence increase in tissue coverage with color mapping feature
-Owning this high-tech feature gives a very positive image of the clinic and of the radiology department to the patients