Zeeshan Ahmed

Emerging biomarkers in cardiovascular disease.

AI-Driven Multi-Omics Approaches for Deciphering Small-Cell Lung Cancer Heterogeneity Using Nucleic-Acid-Based Features

Simple Summary The extensive heterogeneity of small-cell lung cancer (SCLC) across genomic, transcriptomic, epigenetic, proteomic, and microenvironmental levels has continued to undermine precision medicine. This review aims to help understand SCLC biology, resistance, and therapy by utilizing current literature encomp...

Tracing the Heart: An Evidence-Linked Pipeline for Heart-Failure Feature Engineering

The Nimblemind Multi-Agent System is developed, an evidence-linked, rubric-grounded pipeline for automated heart-failure feature engineering, and evaluation was limited to a single-institution cohort and external validation is needed, demonstrating the feasibility of automated, auditable feature engineering for complex...

Recent advances in cardiovascular biomarkers: innovations in early detection, risk prediction, and treatment monitoring.

Recent advances in the application of Machine Learning (ML) techniques to transcriptome datasets of CVD patients are sampled in the hopes of progressing the understanding of underlying pathophysiology, improving the ability to detect disease, and refining the methods of risk stratification of patients.