Thomas J. Flotte, M.D.

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SUMMARY

Thomas J. Flotte, M.D., uses tissue-based approaches to understand melanoma. Specific areas of research interest include correlation of histology with patient outcomes, molecular alterations and biomarker expression. His research goals are to improve tumor diagnosis and develop new therapeutic strategies.

Dr. Flotte is also examining how technology can improve patient care. He is applying information technology and machine learning to assist pathologists in making better and more reproducible diagnoses. Additionally, he is working on cutting-edge technologies to provide new approaches and insights to the study of tissues to create better data that enhance the knowledge of diseases.

Focus areas

• Melanoma. Dr. Flotte does tissue-based research to better understand the underlying biology of pigmented lesions and apply this knowledge to improve patient care. His studies on melanoma include:
  • Correlations of morphological features with clinical outcomes
  • Phenotype-genotype correlations
  • Molecular characterization of pigmented lesions
  • Biomarker discovery
  • Deep learning approaches to diagnosis
• Machine learning. Dr. Flotte applies various machine learning approaches — but particularly deep learning — to whole-slide images. He studies many types of tumors and nontumor diseases. He is developing a suite of tools to assist pathologists with their daily workloads.
• Technology development. Dr. Flotte has been involved in the development of a number of imaging devices and continues to work on improving multispectral imaging, imaging mass spectrometry and multiplexed imaging.
• Clinical informatics. Dr. Flotte uses information technology to improve patient care through clinical decision support, provider order entry and improved imaging.

Significance to patient care

Dr. Flotte's studies will improve patient care by providing better approaches to diagnose and treat patients with melanoma. He is also working to improve patient care by providing pathologists with tools that can assist them in making better and more reproducible diagnoses.