Tobias P. Loka

This study evaluates real-time metagenomic next-generation sequencing (rt-mNGS) for pathogen detection in respiratory samples, showing non-inferiority to culture methods with higher sensitivity and timely results.

This paper predicts decision-making time for diagnosis during NGS cycles using an interpretable machine learning model, achieving over 98% accuracy and reducing turnaround time.

PathoLive detects pathogens in real-time from metagenomic data, improving speed and accuracy by prioritizing clinically relevant hits over contaminants and irrelevant sequences.

This paper introduces a real-time variant calling method during Illumina sequencing that achieves high accuracy and scalability, enabling faster clinical interventions.