Featured Research

from universities, journals, and other organizations

Data-driven machine learning effectively flags risk for post-stroke dangers

Date:
October 3, 2013
Source:
Perelman School of Medicine at the University of Pennsylvania
Summary:
A team of experts in neurocritical care, engineering, and informatics have devised a new way to detect which stroke patients may be at risk of a serious adverse event following a ruptured brain aneurysm.

A team of experts in neurocritical care, engineering, and informatics, with the Perelman School of Medicine at the University of Pennsylvania, have devised a new way to detect which stroke patients may be at risk of a serious adverse event following a ruptured brain aneurysm. This new, data-driven machine learning model, involves an algorithm for computers to combine results from various uninvasive tests to predict a secondary event. Preliminary results were released at the Neurocritical Care Society Annual Meeting in Philadelphia.

Comparing 89 patient cases retrospectively, the team found that automated features of existing ICU data were as effective as the transcranial doppler procedure currently used to detect a dangerous constriction of blood vessels in the brain. Transcranial doppler tests require a skilled technician to be available and are often only conducted once a day, and while the test is selective and accurately detects people who are risk, it is not as efficient (sensitivity of 56%) at ruling out which patients are not at greater risk of this serious adverse event .

"There is a great opportunity to utilize abundant existing data to provide guidance and clinical decision support, as this model was as effective and much less resource-intensive," said senior author Soojin Park, MD, assistant professor of Neurology at Penn. "However, while this simple method may be valuable, most ICUs don't have the IT infrastructure to synergize data in such a way."

The team plans to look at prospective cases to compare this method directly with other assessments and clinical decisions.


Story Source:

The above story is based on materials provided by Perelman School of Medicine at the University of Pennsylvania. Note: Materials may be edited for content and length.


Cite This Page:

Perelman School of Medicine at the University of Pennsylvania. "Data-driven machine learning effectively flags risk for post-stroke dangers." ScienceDaily. ScienceDaily, 3 October 2013. <www.sciencedaily.com/releases/2013/10/131003204950.htm>.
Perelman School of Medicine at the University of Pennsylvania. (2013, October 3). Data-driven machine learning effectively flags risk for post-stroke dangers. ScienceDaily. Retrieved September 16, 2014 from www.sciencedaily.com/releases/2013/10/131003204950.htm
Perelman School of Medicine at the University of Pennsylvania. "Data-driven machine learning effectively flags risk for post-stroke dangers." ScienceDaily. www.sciencedaily.com/releases/2013/10/131003204950.htm (accessed September 16, 2014).

Share This



More Health & Medicine News

Tuesday, September 16, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Man Floats for 31 Hours in Gulf Waters

Man Floats for 31 Hours in Gulf Waters

AP (Sep. 16, 2014) A Texas man is lucky to be alive after he and three others floated for more than a day in the Gulf of Mexico when their boat sank during a fishing trip. (Sept. 16) Video provided by AP
Powered by NewsLook.com
EU Ministers and Experts Meet to Discuss Ebola Reponse

EU Ministers and Experts Meet to Discuss Ebola Reponse

AFP (Sep. 15, 2014) The European Commission met on Monday to coordinate aid that the EU can offer to African countries affected by the Ebola outbreak. Duration: 00:58 Video provided by AFP
Powered by NewsLook.com
Despite The Risks, Antibiotics Still Overprescribed For Kids

Despite The Risks, Antibiotics Still Overprescribed For Kids

Newsy (Sep. 15, 2014) A new study finds children are prescribed antibiotics twice as often as is necessary. Video provided by Newsy
Powered by NewsLook.com
FDA Eyes Skin Shocks Used at Mass. School

FDA Eyes Skin Shocks Used at Mass. School

AP (Sep. 15, 2014) The FDA is considering whether to ban devices used by the Judge Rotenberg Educational Center in Canton, Massachusetts, the only place in the country known to use electrical skin shocks as aversive conditioning for aggressive patients. (Sept. 15) Video provided by AP
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:
from the past week

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins