M. Glaser
Papers
1
Total Citations
4
H-Index
1
About
M. Glaser is a researcher at the forefront of leveraging automation to accelerate real-world evidence (RWE) generation in healthcare. Their key contributions center on developing scalable, automated data collection and processing pipelines, as exemplified by their highly cited work, "PNS271 Automation in Routine Use for Data Collection and Processing for Scalable Faster RWE Generation" (2020). This paper, with 4 citations, demonstrates a practical framework for integrating automation into routine clinical data workflows, significantly reducing the time and manual effort required to generate robust RWE. Glaser's impact lies in bridging the gap between raw healthcare data and actionable insights, enabling faster, more efficient research that can inform clinical decision-making and health policy. Their work is particularly notable for its focus on routine use, ensuring that automation solutions are not just theoretical but directly applicable in real-world settings. By streamlining data collection and processing, Glaser is helping to unlock the full potential of large-scale healthcare databases, paving the way for more agile and evidence-driven medical advancements.
Research Focus
Key Achievements
Top Papers
- 1