The Open Bioinformatics Journal

A Wearable System for the Stress Monitoring of Air Traffic Controllers During An Air Traffic Control Refresher Training and the Trier Social Stress Test: A Comparative Study
Air Traffic Control (ATC) is a complex and demanding process, exposing Air Traffic Controllers (ATCs) to high stress. Recently, efforts have been made in ATC to maintain safety and efficiency in the face of increasing air traffic demands.
A Study on the Relevance of Feature Selection Methods in Microarray Data
This paper studies the relevance of feature selection algorithms in microarray data for effective analysis.
Enhanced Teamwork Communication Model for Electronic Clinical Pathways in Healthcare
One of the main challenges to hospital patient flow and treatment includes the lack of a patient-centered approach, which in turn contributes to non-effective teamwork communication.
Long Non-coding RNAs in the Human Genome Acquired by Horizontal Gene Transfer
Horizontal gene transfer of mobile genetic elements is an essential component of prokaryotic evolution. These insertion events in eukaryotes and particularly in the human genome have been investigated by various methodologies with varying results.
Data Mining Approach to Identify Disease Cohorts from Primary Care Electronic Medical Records: A Case of Diabetes Mellitus
Identification of diseased patients from primary care based electronic medical records (EMRs) has methodological challenges that may impact epidemiologic inferences.
Protein-Protein Interaction Prediction using PCA and SVR-PHCS
Protein-Protein Interactions (PPIs) play a key role in many biological systems. Thus, identifying PPIs is critical for understanding cellular processes. Many experimental techniques were applied to predict PPIs.
Performances of Bioinformatics Pipelines for the Identification of Pathogens in Clinical Samples with the De Novo Assembly Approaches: Focus on 2009 Pandemic Influenza A (H1N1)
Diagnostic assays for pathogen detection are critical components of public-health monitoring efforts. In view of the limitations of methods that target specific agents, new approaches are required for the identification of novel, modified or ‘unsuspected’ pathogens in public-health monitoring schemes.

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Editor's Choice

Data Mining Approach to Identify Disease Cohorts from Primary Care Electronic Medical Records: A Case of Diabetes Mellitus

Ebenezer S. Owusu Adjah, Olga Montvida, Julius Agbeve, Sanjoy K. Paul

Background:

Identification of diseased patients from primary care based electronic medical records (EMRs) has methodological challenges that may impact epidemiologic inferences.

Objective:

To compare deterministic clinically guided selection algorithms with probabilistic machine learning (ML) methodologies for their ability to identify patients with type 2 diabetes mellitus (T2DM) from large population based EMRs from nationally representative primary care database.

Methods:

Four cohorts of patients with T2DM were defined by deterministic approach based on disease codes. The database was mined for a set of best predictors of T2DM and the performance of six ML algorithms were compared based on cross-validated true positive rate, true negative rate, and area under receiver operating characteristic curve.

Results:

In the database of 11,018,025 research suitable individuals, 379 657 (3.4%) were coded to have T2DM. Logistic Regression classifier was selected as best ML algorithm and resulted in a cohort of 383,330 patients with potential T2DM. Eighty-three percent (83%) of this cohort had a T2DM code, and 16% of the patients with T2DM code were not included in this ML cohort. Of those in the ML cohort without disease code, 52% had at least one measure of elevated glucose level and 22% had received at least one prescription for antidiabetic medication.

Conclusion:

Deterministic cohort selection based on disease coding potentially introduces significant mis-classification problem. ML techniques allow testing for potential disease predictors, and under meaningful data input, are able to identify diseased cohorts in a holistic way.

December 12, 2017