Selected Publications
Predicting breast cancer metastasis by using serum biomarkers and clinicopathological data with machine learning technologies
Breast cancer metastasis cannot be detected solely on the basis of surface markers of tumor cells or analytical measurements of single serum biomarkers. A more comprehensive overview of breast cancer may be achieved through the evaluation of a combination of various clinicopathological features. The random-forest-based model presented in this study may be helpful as part of a follow-up intervention decision support system.
In Int J Med Inform.
Rapid Detection of Heterogeneous Vancomycin-Intermediate Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization Time-of-Flight: Using a Machine Learning Approach and Unbiased Validation
hVISA cannot be detected in most clinical microbiology laboratories because the required diagnostic tools are either expensive, time consuming, or labor intensive. To analyze complex MALDI-TOF mass spectra, machine learning (ML) algorithms can be used to generate robust hVISA detection models. We demonstrated that hVISA/VISA could be detected by analyzing MALDI-TOF mass spectra using ML.
In Front Microbiol.
Antihyperglycemic Medications: A Claims-Based Estimate of First-Line Therapy Use Before Initialization of Second-Line Medications
Despite published guidelines, second-line therapy is often initiated without evidence of recommended use of first-line therapy. Apparent treatment failures, which may in fact be attributable to non-adherence to guidelines are common. Point of care and population-level processes are needed to monitor and improve guideline adherence.
In Diabetes Care.
Difference Between Estimated Purchase Price and Insurance Payments for Knee and Hip Implants in Privately Insured Patients Younger Than 65 Years
The total payments insurance companies pay for knee and hip implants were twice as high as the average selling prices at which hospitals purchased the implants from manufacturers, resulting in hundreds of millions of dollars of additional insurance claims.
In JAMA.