BioMark Diagnostics Publishes Peer‑Reviewed Validation of AI‑Driven Lung Cancer Detection Models in *Frontiers in Oncology*

BioMark Diagnostics Inc. has announced that its research on machine learning‑powered models for lung cancer detection has been accepted for publication in the respected scientific journal Frontiers in Oncology. The study, titled “Translational impact of machine learning‑driven predictive modeling with pathway‑based plasma metabolomic biomarkers for lung cancer detection,” highlights the company’s integration of advanced artificial intelligence (AI) and metabolomics to improve early diagnostic accuracy. The published work reflects BioMark’s strategic use of pathway‑level metabolic data combined with machine learning to interpret complex biochemical signatures linked to early‑stage lung cancer. This method goes beyond traditional single biomarker approaches, providing a more holistic and precise understanding of disease signals in blood plasma. BioMark’s research team collaborated with Dr. Maria Vaida and colleagues at Harrisburg University of Science and Technology, using tools like the Human Metabolome Database and interpretability techniques such as SHAP analysis to explore how metabolic pathways contribute to cancer detection. Company CEO Rashid Ahmed Bux described the acceptance as a “pivotal moment” that validates years of investment in AI and machine learning infrastructure, confirming the scientific rigor and potential clinical relevance of these predictive models. The full paper is expected to be published later this month and available on BioMark’s website. #BioMarkDiagnostics #LungCancerAI #EarlyDetection #FrontiersInOncology #SlimScan #GrowthStocks #CANSLIM