Articles
Assess MPS II Diagnosis and Treatment Referral Pathways and Identify Potential Patients via Predictive Modeling
Top features from the designed predictive model align well with the human phenotype ontology associations for MPS II. The top treatment centers across the country for MPS II patients based on patient volume and mapped referrals.
Finding APDS Patients Using Predictive Models
Summary of typical APDS symptoms (left) and importance of features output by the predictive model for patients over the age of 12 (right).
Machine Learning Model Using Insurance Claims Data to Help Predict ALS Diagnosis
Poster presented at Mayo Clinic Annual Conference 2019 outlining model performance and feature importance in the prediction of future ALS diagnosis.
Predictive Modeling for Treatment of Relapsing-Remitting Multiple Sclerosis (RRMS)
SHAP values of factors influencing the first-line class of DMTs of treated patients.
Assessing the Telehealth Treatment Landscape and Building Predictive Models (AI/ML) to Identify Patients/Providers Most Likely to Use Telehealth
Patient segments were identified using telehealth proactivity and telehealth accessibility as the two major axes.
Identifying Potential High-Risk Factor Arrhythmia Patients Using Predictive Modeling
Top predictive features of arrhythmias from the diabetes patient model. Plots demonstrate the positive correlation between age and predictive importance. Plots demonstrate the positive correlation between months from initial diabetes diagnosis and predictive importance.
Scoring and Segmenting Key Opinion Leader Physicians With Innovative and Customizable Machine Learning Techniques
Five segments of healthcare providers based specifically on the likelihood of adopting the oncology product for first line use.
Improving an AATD Predictive Model Using EMR Data
SHAP values of top features from the highest-performing predictive model, including diagnoses, lab results and location of service factors.
Use of Machine Learning to Identify Gastroparesis Patients Suitable for Nasal Spray Metoclopramide
Poster presented at Digestive Disease Week 2023 outlining model performance, feature importance and patient clustering in gastroparesis patients suitable for nasal spray metoclopramide.
Predictive Modeling for Treatment Switching in Paroxysmal Nocturnal Hemoglobinuria (PNH) Patients
Plots comparing feature importance between the patient-based model, the physician-based model and the hybrid patient-physician-based model.