Doc Forre Science Report – Edition 1 [SUB]

This has been a pretty awesome last couple weeks for the Medical Technology side of the news, so this week’s update is going to be a little bit more focused than the first Report. I apologize for nothing.

Medical Technology

Researchers at NYU have developed a new, non-invasive, objective test for getting a quick idea of severity of head trauma in patients… using Michael Jackson and The Lion King.

The device:  An eye-tracking setup that displays music videos in one-eighth of the screen, rotating like a clock-hand, for 220 seconds.

The hallmark of many neurological disorders, particularly head trauma, is dysfunction in eye movement; this is why doctors make you follow their finger with your eyes. This method of gauging neurological function hasn’t changed in pretty much forever, but it does come with a degree of subjectivity. And as the authors mention in their study, small children aren’t always going to cooperate.

Only 200 seconds of the data is needed for the algorithm to do its work, but its work is solid. The subject pool was fairly large, with 75 trauma patients in the ER vs around 65 control participants who were selected on a volunteer basis. The 75 were further broken down by severity of actual trauma based on whether or not they qualified for a CT scan and how visible the trauma was on said scan. The correlation was strong.

The study can be read online here and was published in the Journal of Neurotrauma.

Medical Technology and AI

Drug development is a problem. It tends to be funded primarily by drug companies, with the intention of making a few dollars off of the results (a reasonable plan). If the resulting drug won’t be much of a money maker, why fund the research (an unreasonable plan). It also tends to require a lot of time and effort, and many new compounds have to get glossed over for the sake of studying a few prime-candidate.

A team at Cambridge has announced that they have developed a robot that automates the early stages of drug development. Using machine learning and robotics, “Eve” can test the effectiveness of up to 10,000 compounds per day, and incorporate knowledge of successes and failures into testing new compounds.

What diseases are they currently targeting? Tropical ones, such as African sleeping sickness. With a low potential income, these diseases just aren’t as cost-effective to develop treatments for. With a device such as Eve reducing time and costs of early drug development, she presents a prime solution to the problem.

The full study can be read here, and was published by The Royal Society:  Interface.

Medical Technology

Speaking of medical difficulties in developing nations, another major advancement was made on a smaller scale. Columbia University engineers have developed a smartphone dongle and app that can screen a small blood sample for HIV and syphilis using minimal space and electricity.

The device uses only a finger-prick’s worth of blood, and cuts electricity consumption by using mechanically activated components where it can. Any remaining electricity needs are supplied by the phone itself.

Similar units cost nearly $20,000 to build for a lab; this device costs $34 to manufacture, and from the look of the device, is barely larger than the smartphone that powers it.

This research was published in Science Translational Medicine.


Doc Forre is not a real doctor, nor even a fake one – he just plays one in Shadowrun. His interests are sciences with unnecessary neuro- prefixes and how they can be abused in traditional game design. You can get in touch with Doc Forre via email at azuletech@gmail.com or follow him on twitter @DocForre.

Share This Post
Written by Zymepunk
Zymepunk was drawn into the world of cyberpunk by Deus Ex and Blade Runner and now looks both back and forwards in time for anything that may come close to those masterpieces.

Leave a Reply

Your email address will not be published.

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>