AIMC Topic: Odds Ratio

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Catch Me if You Can: Acute Events Hidden in Structured Chronic Disease Diagnosis Descriptions Show Detectable Recording Patterns in EHR.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Our previous research shows that structured cancer DX description data accuracy varied across electronic health record (EHR) segments (e.g. encounter DX, problem list, etc.). We provide initial evidence corroborating these findings in EHRs from patie...

Robot-assisted technique vs conventional freehand technique in spine surgery: A meta-analysis.

International journal of clinical practice
BACKGROUND: The impact of robot-assisted techniques versus conventional freehand techniques in terms of the accuracy of pedicle screw placement remains conflicting. This meta-analysis was performed to evaluate this relationship.

Electromechanical-assisted training for walking after stroke.

The Cochrane database of systematic reviews
BACKGROUND: Electromechanical- and robot-assisted gait-training devices are used in rehabilitation and might help to improve walking after stroke. This is an update of a Cochrane Review first published in 2007 and previously updated in 2017.

Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

Journal of diabetes research
BACKGROUND: An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and the number continues to grow, placing a huge burden on the healthcare system, especially in those remote, underserved areas...

Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk.

Scientific reports
To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Several ...

Investigating cooperation with robotic peers.

PloS one
We explored how people establish cooperation with robotic peers, by giving participants the chance to choose whether to cooperate or not with a more/less selfish robot, as well as a more or less interactive, in a more or less critical environment. We...

A machine learning approach for predictive models of adverse events following spine surgery.

The spine journal : official journal of the North American Spine Society
BACKGROUND: Rates of adverse events following spine surgery vary widely by patient-, diagnosis-, and procedure-related factors. It is critical to understand the expected rates of complications and to be able to implement targeted efforts at limiting ...