Augmented reality microscopy to bridge trust between AI and pathologists.

Sunil Badve¹, George L Kumar², Tobias Lang³, Eli Peigin⁴, James Pratt⁵, Robert Anders⁶, Deyali Chatterjee⁷, Raul S Gonzalez⁸, Rondell P Graham⁹, Alyssa M Krasinskas⁸, Xiuli Liu¹⁰, Alexander Quaas¹¹, Romil Saxena⁸, Namrata Setia¹², Laura Tang¹³, Hanlin L Wang¹⁴, Josef Rüschoff¹⁵, Hans-Ulrich Schildhaus¹⁵, Khalid Daifalla¹⁶, Marc Päpper¹⁶, Patrick Frey¹⁶, Felix Faber¹⁶, Maria Karasarides¹⁷

¹Emory University School of Medicine, Atlanta, GA, USA. sbadve@emory.edu.

²Bristol Myers Squibb, Princeton, NJ, USA. george.kumar@astrazeneca.com.

³Mindpeak, Hamburg, Germany. tobias.lang@mindpeak.ai.

⁴Augmentiqs, D.N, Misgav, Israel.

⁵Bristol Myers Squibb, Princeton, NJ, USA.

⁶Johns Hopkins University Baltimore, Baltimore, MD, USA.

⁷MD Anderson Cancer Center, Houston, TX, USA.

⁸Emory University School of Medicine, Atlanta, GA, USA.

⁹Mayo Clinic, Rochester, MN, USA.

¹⁰Washington University School of Medicine, St Louis, MO, USA.

¹¹Cologne University Hospital, Cologne, Germany.

¹²University of Chicago, Chicago, IL, USA.

¹³Memorial Sloan Kettering Cancer Center, New York, NY, USA.

¹⁴UCLA David Geffen School of Medicine, Los Angeles, CA, USA.

¹⁵Discovery Life Sciences Biomarker Services GmbH, Kassel, Germany.

¹⁶Mindpeak, Hamburg, Germany.

¹⁷Bristol Myers Squibb, Princeton, NJ, USA. maria@delphina.io.

PubMed PMC DOI PDF

Abstract

Diagnostic certainty is the cornerstone of modern medicine and critical for maximal treatment benefit. When evaluating biomarker expression by immunohistochemistry (IHC), however, pathologists are hindered by complex scoring methodologies, unique positivity cut-offs and subjective staining interpretation. Artificial intelligence (AI) can potentially eliminate diagnostic uncertainty, especially whe…

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