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OHDSI Europe | Lung Cancer Patient Treatment with Immune Checkpoint Inhibitors: Multicenter, NLP-guided Data Extraction from EHRs
Analysis of Lung Cancer Patient Treatment with Immune Checkpoint Inhibitors Using Natural Language Processing for Data Extraction from Electronic Health Records
European Lung Cancer Congress | Poster | Real-World Evidence of Immune Checkpoint Inhibitor Treatment in Lung Cancer Patients from a Belgian Multicenter Study
Discover the initial findings of the ICI-treated lung cancer patient cohort of 730+ patients regarding demographic and clinical characteristics, ICI treatments, and overall survival (OS).
ESMO Immuno-Oncology | Poster | Real-World Insights on Pan-Cancer Immune Checkpoint Inhibitor Treatment: Initial Findings of a Belgian Multicenter Study
To bridge the gap between clinical trial patients and real-world populations, we conducted a comprehensive study in Belgium to characterize cancer patients treated with immune checkpoint inhibitors (ICIs), which have demonstrated survival advantages in various cancer types.
ISPOR Europe | Poster | Building Federated Data Networks with Common Data Models to Generate Insights through Real-World Evidence Observational Studies in Oncology
Accessing and standardizing raw clinical data across multiple hospitals presents a challenge in Oncology. However, it is crucial to use real-world data sources such as electronic health records (EHR) to leverage untapped information. We are building a federated data network to facilitate GDPR-compliant data exchange of large datasets, with hospitals as owners. This network, governed by a common data model (CDM), is aimed at fostering multicenter, observational, real-world evidence (RWE) studies in Oncology, with breast cancer, lung cancer, and immunotherapy as therapeutic areas of focus.
ESMO MAP | Poster | Automatic data processing to identify EGFR mutations in pathology reports of patients with non-small cell lung cancer (NSCLC)
NLP algorithms allow rapid data extraction from pathology reports, thereby offering a time-efficient and cost-effective alternative to manual data processing. In turn, this approach enables rapid insight in current biomarker testing rates and prevalence of (actionable) mutations.
ESC Heart Failure | Publication | Detection of ATTR-CM by automated data extraction from EHRs
Information held in Electronic Health Records (EHRs) hold a significant opportunity to provide physicians and researchers with better and more insights to improve disease management and treatment.
OHDSI Europe | Poster | Automated retrospective data extraction from EHRs using NLP creating an OMOP-CDM database
The study aimed to analyze individuals with ATTR-CM in a real-world heart failure patient population using a federated OMOP-CDM database generated from data of electronic health records.
ESC Heart Failure | Publication | Cardio–renal–metabolic syndrome: clinical features and dapagliflozin eligibility in a real-world heart failure cohort
An example of the power of real-world data, technology and collaboration to transform patient care. The study aimed to shed light on patient eligibility for SGLT2 inhibitors as a therapy for heart failure patients, providing valuable information for clinicians and researchers.
HEART | Publication | Prevalence, outcomes and costs of a contemporary, multinational population with heart failure
A large multi-country Real-World Evidence study in heart failure shows that 1–2% of the contemporary adult population has heart failure. Through analyzing data from both national registries and Electronic Health Records, further insights into the burden of heart failure on patients and on our healthcare systems can be gained.
Journal of the Peripheral Nervous System | Publication | Better screening of patients for rare diseases through an NLP algorithm
A clinically-validated NLP algorithm offers a valid and accurate tool to detect red flag symptoms in medical records across multiple disciplines, supporting better screening for patients with rare diseases.
Publication | Direct anterior approach for total hip arthroplasty using the “bikini incision”
LynxCare’s data insights enabled the detection of unknown transient events associated with direct anterior approach total hip arthroplasty.
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