Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Future medical conditions predicted with new statistical model

04.06.2012
Analyzing medical records from thousands of patients, statisticians have devised a statistical model for predicting what other medical problems a patient might encounter.

Like how Netflix recommends movies and TV shows or how Amazon.com suggests products to buy, the algorithm makes predictions based on what a patient has already experienced as well as the experiences of other patients showing a similar medical history.

"This provides physicians with insights on what might be coming next for a patient, based on experiences of other patients. It also gives a predication that is interpretable by patients," said Tyler McCormick, an assistant professor of statistics and sociology at the University of Washington.

The algorithm will be published in an upcoming issue of the journal Annals of Applied Statistics. McCormick's co-authors are Cynthia Rudin, Massachusetts Institute of Technology, and David Madigan, Columbia University.

McCormick said that this is one of the first times that this type of predictive algorithm has been used in a medical setting. What differentiates his model from others, he said, is that it shares information across patients who have similar health problems. This allows for better predictions when details of a patient's medical history are sparse.

For example, new patients might lack a lengthy file listing ailments and drug prescriptions compiled from previous doctor visits. The algorithm can compare the patient's current health complaints with other patients who have a more extensive medical record that includes similar symptoms and the timing of when they arise. Then the algorithm can point to what medical conditions might come next for the new patient.

"We're looking at each sequence of symptoms to try to predict the rest of the sequence for a different patient," McCormick said. If a patient has already had dyspepsia and epigastric pain, for instance, heartburn might be next.

The algorithm can also accommodate situations where it's statistically difficult to predict a less common condition. For instance, most patients do not experience strokes, and accordingly most models could not predict one because they only factor in an individual patient's medical history with a stroke. But McCormick's model mines medical histories of patients who went on to have a stroke and uses that analysis to make a stroke prediction.

The statisticians used medical records obtained from a multiyear clinical drug trial involving tens of thousands of patients aged 40 and older. The records included other demographic details, such as gender and ethnicity, as well as patients' histories of medical complaints and prescription medications.

They found that of the 1,800 medical conditions in the dataset, most of them – 1,400 – occurred fewer than 10 times. McCormick and his co-authors had to come up with a statistical way to not overlook those 1,400 conditions, while alerting patients who might actually experience those rarer conditions.

They came up with a statistical modeling technique that is grounded in Bayesian methods, the backbone of many predictive algorithms. McCormick and his co-authors call their approach the Hierarchical Association Rule Model and are working toward making it available to patients and doctors.

"We hope that this model will provide a more patient-centered approach to medical care and to improve patient experiences," McCormick said.

The work was funded by a Google Ph.D. fellowship awarded to McCormick and by the National Science Foundation.

For more information, contact McCormick at 206-221-6981 or tylermc@uw.edu. Download the Annals of Applied Statistics paper from McCormick's website: http://www.stat.washington.edu/~tylermc/

Molly McElroy | EurekAlert!
Further information:
http://www.uw.edu

More articles from Studies and Analyses:

nachricht New study: How does Europe become a leading player for software and IT services?
03.04.2017 | Fraunhofer-Institut für System- und Innovationsforschung (ISI)

nachricht Reusable carbon nanotubes could be the water filter of the future, says RIT study
30.03.2017 | Rochester Institute of Technology

All articles from Studies and Analyses >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Can the immune system be boosted against Staphylococcus aureus by delivery of messenger RNA?

Staphylococcus aureus is a feared pathogen (MRSA, multi-resistant S. aureus) due to frequent resistances against many antibiotics, especially in hospital infections. Researchers at the Paul-Ehrlich-Institut have identified immunological processes that prevent a successful immune response directed against the pathogenic agent. The delivery of bacterial proteins with RNA adjuvant or messenger RNA (mRNA) into immune cells allows the re-direction of the immune response towards an active defense against S. aureus. This could be of significant importance for the development of an effective vaccine. PLOS Pathogens has published these research results online on 25 May 2017.

Staphylococcus aureus (S. aureus) is a bacterium that colonizes by far more than half of the skin and the mucosa of adults, usually without causing infections....

Im Focus: A quantum walk of photons

Physicists from the University of Würzburg are capable of generating identical looking single light particles at the push of a button. Two new studies now demonstrate the potential this method holds.

The quantum computer has fuelled the imagination of scientists for decades: It is based on fundamentally different phenomena than a conventional computer....

Im Focus: Turmoil in sluggish electrons’ existence

An international team of physicists has monitored the scattering behaviour of electrons in a non-conducting material in real-time. Their insights could be beneficial for radiotherapy.

We can refer to electrons in non-conducting materials as ‘sluggish’. Typically, they remain fixed in a location, deep inside an atomic composite. It is hence...

Im Focus: Wafer-thin Magnetic Materials Developed for Future Quantum Technologies

Two-dimensional magnetic structures are regarded as a promising material for new types of data storage, since the magnetic properties of individual molecular building blocks can be investigated and modified. For the first time, researchers have now produced a wafer-thin ferrimagnet, in which molecules with different magnetic centers arrange themselves on a gold surface to form a checkerboard pattern. Scientists at the Swiss Nanoscience Institute at the University of Basel and the Paul Scherrer Institute published their findings in the journal Nature Communications.

Ferrimagnets are composed of two centers which are magnetized at different strengths and point in opposing directions. Two-dimensional, quasi-flat ferrimagnets...

Im Focus: World's thinnest hologram paves path to new 3-D world

Nano-hologram paves way for integration of 3-D holography into everyday electronics

An Australian-Chinese research team has created the world's thinnest hologram, paving the way towards the integration of 3D holography into everyday...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

Marine Conservation: IASS Contributes to UN Ocean Conference in New York on 5-9 June

24.05.2017 | Event News

AWK Aachen Machine Tool Colloquium 2017: Internet of Production for Agile Enterprises

23.05.2017 | Event News

Dortmund MST Conference presents Individualized Healthcare Solutions with micro and nanotechnology

22.05.2017 | Event News

 
Latest News

How herpesviruses win the footrace against the immune system

26.05.2017 | Life Sciences

Water forms 'spine of hydration' around DNA, group finds

26.05.2017 | Life Sciences

First Juno science results supported by University of Leicester's Jupiter 'forecast'

26.05.2017 | Physics and Astronomy

VideoLinks
B2B-VideoLinks
More VideoLinks >>>