Improving pathology diagnosis using advanced machine learning techniques

Advancing Digital Pathology through Novel Machine Learning Methodologies

NIH-funded research Dartmouth College · NIH-11090503

This study is working on using advanced computer technology to help doctors who look at microscope images for diagnosing diseases, making their job easier and more accurate, especially when it comes to rare conditions.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionDartmouth College NIH-funded
Lab location1 site (Hanover, United States)
Project IDNIH-11090503 on NIH RePORTER

What this research studies

This research focuses on enhancing the accuracy and efficiency of pathology diagnoses by utilizing novel machine learning methodologies. It aims to reduce the cognitive burden on pathologists by automating the analysis of microscopy images, which are crucial for diagnosing various medical conditions. The project will develop generative adversarial networks to create augmented datasets that include rare and challenging histopathological patterns, ultimately improving diagnostic capabilities. By addressing the limitations of current methods, this research seeks to standardize and streamline the pathology workflow.

Who could benefit from this research

Good fit: Ideal candidates for this research are patients undergoing diagnostic procedures that involve histopathological analysis, particularly those with rare or complex conditions.

Not a fit: Patients whose conditions do not require histopathological evaluation or those not undergoing tissue analysis may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more accurate and timely diagnoses for patients, improving treatment outcomes.

How similar studies have performed: Other research has shown promising results using machine learning in pathology, indicating that this approach has potential for significant advancements.

Where this research is happening

Hanover, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-09 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.