Publications

An up-to-date list of publications can be found on my Google Scholar profile.

1. Scaffolding for success: Blending learning with and about Generative AI in medical education
   Medical Teacher (2025)
   Boman, M., Jhun, P., & Schaekermann, M.
   [Google Research Blog]

2. Exploring Large Language Models for Specialist-Level Oncology Care
   New England Journal of Medicine (NEJM) AI (2025)
   Palepu, A., Dhillon, V., Niravath, P., Weng, W.-H., Prasad, P., Saab, K., Tanno, R., Cheng, Y., Mai, H., Burns, E., Ajmal, Z., Kulkarni, K., Mansfield, P., Webster, D., Barral, J., Gottweis, J., Schaekermann, M., Mahdavi, S., Natarajan, V., Karthikesalingam, A., & Tu, T.
   [Google Research Blog]

3. Towards Better Health Conversations: The Benefits of Context-seeking
   Under Review (2025)
   Sayres, R., Hao, Y., Ward, A., Wang, A., Freeman, B., Zhan, S., Ardila, D., Li, J., Lee, I.-C., Iurchenko, A., Kou, S., Badola, K., Hu, J., Kumar, B., Johnson, K., Vijay, S., Krogue, J., Hassidim, A., Matias, Y., Webster, D. R., Virmani, S., Liu, Y., Duong, Q., & Schaekermann, M.
   [Last Author]
   [Google Research Blog]

4. Towards physician-centered oversight of conversational diagnostic AI
   Under Review (2025)
   Vedadi, E., Barrett, D., Harris, N., Wulczyn, E., Reddy, S., Ruparel, R., Schaekermann, M., Strother, T., Tanno, R., Sharma, Y., Lee, J., Hughes, C., Slack, D., Palepu, A., Freyberg, J., Saab, K., Liévin, V., Weng, W.-H., Tu, T., Liu, Y., Tomasev, N., Kulkarni, K., Mahdavi, S., Guu, K., Barral, J., Webster, D. R., Manyika, J., Hassidim, A., Chou, K., Matias, Y., Kohli, P., Rodman, A., Natarajan, V., Karthikesalingam, A., & Stutz, D.
   [Google Research Blog]

5. Advancing Conversational Diagnostic AI with Multimodal Reasoning
   Under Review (2025)
   Saab, K., Freyberg, J., Park, C.-J., Strother, T., Cheng, Y., Weng, W.-H., Barrett, D., Stutz, D., Tomasev, N., Palepu, A., Liévin, V., Sharma, Y., Ruparel, R., Ahmed, A., Vedadi, E., Kanada, K., Hughes, C., Liu, Y., Brown, G., Gao, Y., Li, S., Mahdavi, S., Manyika, J., Chou, K., Matias, Y., Hassidim, A., Webster, D. R., Kohli, P., Eslami, S. M., Barral, J., Rodman, A., Natarajan, V., Schaekermann, M., Tu, T., Karthikesalingam, A., & Tanno, R.
   [Google Research Blog]

6. Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities
   arXiv (2025)
   Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., Marris, L., Petulla, S., Gaffney, C., Aharoni, A., Lintz, N., Cardal Pais, T., Jacobsson, H., Szpektor, I., Jiang, N., Haridasan, K., Omran, A., Saunshi, N., Bahri, D., Mishra, G., Chu, E., Boyd, T., Hekman, B., Parisi, A., Zhang, C., Kawintiranon, K., Bedrax-Weiss, T., Wang, O., Xu, Y., Purkiss, O., Mendlovic, U., Deutel, I., Nguyen, N., Langley, A., Korn, F., Rossazza, L., Ramé, A., Waghmare, S., Miller, H. and 3384 other authors
   [The "M" in Gemini and part of the first-name-initials easter egg in the author list 🐣]
   [Google Keyword Blog]

7. Towards Conversational AI for Disease Management
   Under Review (2025)
   Palepu, A., Liévin, V., Weng, WH., Saab, K., Stutz, D., Cheng, Y., Kulkarni, K., Mahdavi, S.S., Barral, J., Webster, D. R., Chou, K., Hassidim, A., Matias, Y., Manyika, J., Tanno, R., Natarajan, V., Rodman, A., Tu, T., Karthikesalingam, A.*, & Schaekermann, M.* (2025)
   [*Co-last Author]
   [Google Research Blog]

8. Towards Conversational Diagnostic AI
   Nature (2025)
   Tu, T.*, Schaekermann, M.*, Palepu, A.*, Saab, K., Freyberg, J., Tanno, R., Wang, A., Li, B., Amin, M., Tomasev, N., Azizi, S., Singhal, K., Cheng, Y., Hou, L., Webson, A., Kulkarni, K., Mahdavi, S. S., Semturs, C., Gottweis, J., Barral, J., Chou, K., Corrado, G.S., Matias, Y., Karthikesalingam, A., & Natarajan, V.
   [*Co-first Author]
   [Google Research Blog]

9. Towards Accurate Differential Diagnosis with Large Language Models
   Nature (2025)
   McDuff, D.*, Schaekermann, M.*, Tu, T.*, Palepu, A.*, Wang, A., Garrison, J., Singhal, K., Sharma, Y., Azizi, S., Kulkarni, K., Hou, L., Cheng, Y., Liu, Y., Mahdavi, S. S., Prakash, S., Pathak, A., Semturs, C., Patel, S., Webster, D. R., Dominowska, E., Gottweis, J., Barral, J., Chou, K., Corrado, G.S., Matias, Y., Sunshine, J., Karthikesalingam, A., & Natarajan, V.
   [*Co-first Author]
   [Google Research Blog]

10. Generative AI for medical education: Insights from a case study with medical students and an AI tutor for clinical reasoning.
    CHI Extended Abstracts (2025)
    Wang, A., Ruparel, R., Iurchenko, A., Jhun, P., Séguin, J. A., Strachan, P., Wong, R., Karthikesalingam, A., Matias, Y., Hassidim, A., Webster, A., Semturs, C., Krause, J., & Schaekermann, M.
    [Last Author]
    [Google Research Blog]

11. Conversational AI in health: Design considerations from a Wizard-of-Oz dermatology case study with users, clinicians and a medical LLM
    CHI Extended Abstracts (2024)
    Li, B., Wang, A., Strachan, P., Séguin, J. A., Lachgar, S., Schroeder, K. C., Fleck, M. S., Wong, R., Karthikesalingam, A., Natarajan, V., Matias, Y., Corrado, G. S., Webster, D., Liu, Y., Hammel, N., Sayres, R., Semturs, C.*, & Schaekermann, M.*
    [*Co-Last Author]

12. LearnLM: Improving Gemini for Learning
    arXiv (2025)
    Modi, A., Veerubhotla, A. S., Rysbek, A., Huber, A., Wiltshire, B., Veprek, B., Gillick, D., Kasenberg, D., Ahmed, D., Jurenka, I., Cohan, J., She, J., Wilkowski, J., Alarakyia, K., McKee, K. R., Wang, L., Kunesch, M., Schaekermann, M., Pîslar, M., Joshi, N., Mahmoudieh, P., Jhun, P., Wiltberger, S., Mohamed, S., Agarwal, S., Phal, S. M., Lee, S. J., Strinopoulos, T., Ko, W.-J., Wang, A., Anand, A., Bhoopchand, A., Wild, D., Pandya, D., Bar, F., Graham, G., Winnemoeller, H., Nagda, M., Kolhar, P., Schneider, R., Zhu, S., Chan, S., Yadlowsky, S., Sounderajah, V., & Assael, Y.
    [Google Research Blog]

13. Towards Expert-Level Medical Question Answering with Large Language Models
    Nature Medicine (2025)
    Singhal, K., Tu, T., Gottweis, J., Sayres, R., Wulczyn, E., Hou, L., Clark, K., Pfohl, S., Cole-Lewis, H., Neal, D., Schaekermann, M., Wang, A., Amin, M., Lachgar, S., Mansfield, P., Prakash, S., Green, B., Dominowska, E., Arcas, B. A. y, Tomasev, N., Liu, Y., Wong, R., Semturs, C., Mahdavi, S. S., Barral, J., Webster, D., Corrado, G. S., Matias, Y., Azizi, S., Karthikesalingam, A., & Natarajan, V.
    [Google Cloud Blog] [Med-PaLM Website]

14. Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study
    The Lancet eClinicalMedicine (2024)
    Schaekermann, M.*, Spitz, T.*, Pyles, M.*, Cole-Lewis, H., Wulczyn, E., Pfohl, S.R., Martin, D. Jr., Jaroensri, R., Keeling, G., Liu, Y., Farquhar, S., Xue, Q., Lester, J., Hughes, C., Strachan, P., Tan, F., Bui, P., Mermel, C. H., Peng, L. H., Matias, Y., Corrado, G. S., Webster, D. R., Virmani, S., Semturs, C., Liu, Y., Horn, I., & Chen, P. H. C.
    [*Co-first Author]
    [Google Research Blog] [Google Keyword Blog]

15. A toolbox for surfacing health equity harms and biases in large language models
    Nature Medicine (2024)
    Pfohl, S. R., Cole-Lewis, H., Sayres, S., Neal, D., Asiedu, M., Dieng, A., Tomasev, N., Rashid, Q. M., Azizi, S., Rostamzadeh, N., McCoy, L. G., Celi, L. A., Liu, Y., Schaekermann, M., Walton, A., Parrish, A., Nagpal, C., Singh, P., Dewitt, A., Mansfield, P., Prakash, S., Heller, K., Karthikesalingam, A., Semturs, C., Barral, J., Corrado, G., Matias, Y., Smith-Loud, J., Horn, I., & Singhal, K.
    [Google Keyword Blog]

16. Capabilities of Gemini Models in Medicine
    arXiv (2024)
    Saab, K., Tao, T., Weng, W., Tanno, R., Stutz, D., Wulczyn, E., Zhang, F., Strother, T., Park, C., Vedadi, E., Chaves, J. Z., Hu, S., Schaekermann, M., Kamath, A., Cheng, Y., Barrett, D. G. T., Cheung, C., Mustafa, B., Palepu, A., McDuff, D., Hou, L., Golany, T., Liu, L., Alayrac, J., Houlsby, N., Tomasev, N., Freyberg, J., Lau, C., Kemp, J., Lai, J., Azizi, S., Kanada, K., Man, S., Kulkarni, K., Sun, R., Shakeri, S., He, L., Caine, B., Webson, A., Latysheva. N., Johnson, M., Mansfield, P., Lu, J., Rivlin, E., Anderson, J., Green, B., Wong, R., Krause, J., Shlens, J., Dominowska, E., Eslami, S. M. A., Chou, K., Cui, C., Vinyals, O., Kavukcuoglu, K., Manyika, J., Dean, J., Hassabis, D., Matias, Y., Webster, D., Barral, J., Corrado, G., Semturs, C., Mahdavi, S. S., Gottweis, J., Karthikesalingam, A., & Natarajan, V.
    [Google Research Blog]

17. Towards Generalist Biomedical AI
    New England Journal of Medicine (NEJM) AI (2023)
    Tu, T., Azizi, S., Driess, D., Schaekermann, M., Amin, M., Chang, P.-C., Carroll, A., Lau, C., Tanno, R., Ktena, I., Mustafa, B., Chowdhery, A., Liu, Y., Kornblith, S., Fleet, D., Mansfield, P., Prakash, S., Wong, R., Virmani, S., Semturs, C., Mahdavi, S. S., Green, G., Dominowska, E., Arcas, B. A. y, Barral, J., Webster, D., Corrado, G. S., Matias, Y., Singhal, K., Florence, P., Karthikesalingam, A., & Natarajan, V.
    [Google Research Blog]

18. Collaboration between clinicians and vision–language models in radiology report generation
    Nature Medicine (2024)
    Tanno, R., Barrett, D. G. T., Sellergren, A., Ghaisas, S., Dathathri, S., See, A., Welbl, J., Singhal, K., Azizi, S., Tu, T., Schaekermann, M., May, R., Lee, R., Man, S., Ahmed, Z., Mahdavi, S. S., Matias, Y., Barral, J., Eslami, A., Belgrave, D., Natarajan, V., Shetty, S., Kohli, P., Huang, P., Karthikesalingam, A., & Ktena, I.

19. MINT: A wrapper to make multi-modal and multi-image AI models interactive
    arXiv (2024)
    Freyberg, J., Roy, A. G., Spitz, T., Freeman, B., Schaekermann, M., Strachan, P., Schnider, E., Wong, R., Webster, D. R., Karthikesalingam, A., Liu, Y., Dvijotham, K., & Telang, U.

20. Evaluating AI systems under uncertain ground truth: a case study in dermatology
    Medical Image Analysis (2023)
    Stutz, D., Cemgil, A. T., Roy, A. G., Matejovicova, T., Barsbey, M., Strachan, P., Schaekermann, M., Freyberg, J., Rikhye, R., Freeman, B., Matos, J. P., Telang, U., Webster, D. R., Liu, Y., Corrado, G. S., Matias, Y., Kohli, P., Liu, Y., Doucet, A., & Karthikesalingam, A.

21. Data Excellence for AI: Why Should You Care?
    Interactions (2022)
    Aroyo, L., Lease, M., Paritosh, P., & Schaekermann, M.

22. Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study
    The Lancet Digital Health (2022)
    Ruamviboonsuk, P., Tiwari, R., Sayres, R., Nganthavee, V., Hemarat, K., Kongprayoon, A., Raman, R., Levinstein, B., Liu, Y., Schaekermann, M., Lee, R., Virmani, S., Widner, K., Chambers, J., Hersch, F., Peng, L., & Webster, D. R.

23. In Search of Ambiguity: A Three-Stage Workflow Design to Clarify Annotation Guidelines for Crowd Workers
    Frontiers in Artificial Intelligence (2022)
    Pradhan, V. K., Schaekermann, M., & Lease, M.

24. Investigating and Mitigating Biases in Crowdsourced Data
    Co-organizer of CSCW Workshop (2021)
    Hettiachchi, D., Sanderson, M., Goncalves, J., Hosio, S., Kazai, G., Lease, M., Schaekermann, M., & Yilmaz, E.

25. The Challenge of Variable Effort Crowdsourcing and How Visible Gold Can Help
    CSCW (2021)
    Hettiachchi, D., Schaekermann, M., McKinney, T. J., & Lease, M.

26. Human-AI Interaction in the Presence of Ambiguity: From Deliberation-based Labeling to Ambiguity-aware AI
    Doctoral Thesis, University of Waterloo, Canada (2020)
    Schaekermann, M.

27. Ambiguity-aware AI Assistants for Medical Data Analysis
    CHI (2020)
    Schaekermann, M., Beaton, G., Sanoubari, E., Lim, A., Larson, K., & Law, E.
    [First Author]

28. Expert Discussions Improve Comprehension of Difficult Cases in Medical Image Assessment
    CHI (2020)
    Schaekermann, M., Cai, C. J., Huang, A. E., & Sayres, R.
    [First Author]

29. Longitudinal Screening for Diabetic Retinopathy in a Nationwide Screening Program: Comparing Deep Learning and Human Graders
    Journal of Diabetes Research (2020)
    Limwattanayingyong, J., Nganthavee, V., Seresirikachorn, K., Singalavanija, T., Soonthornworasiri, N., Ruamviboonsuk, V., Rao, C., Raman, R., Grzybowski, A., Schaekermann, M., Peng, L. H., Webster, D. R., Semturs, C., Krause, J., Sayres, R., Hersch, F., Tiwari, R., Liu, Y., & Ruamviboonsuk, P.

30. Place Your Bets: Will Machine Learning Outgrow Human Labeling?
    AI Magazine (2020)
    Schaekermann, M., Homan, C. M., Aroyo, L., Paritosh, P., Bollacker, K., & Welty, C.
    [First Author]

31. Tablet‐based electroencephalography diagnostics for patients with epilepsy in the West African Republic of Guinea
    European Journal of Neurology (2020)
    Sokolov, E., Abdoul Bachir, D. H., Sakadi, F., Williams, J., Vogel, A. C., Schaekermann, M., Tassiou, N., Bah, A. K., Khatri, V., Hotan, G. C., Ayub, N., Leung, E., Fantaneanu, T. A., Patel, A., Vyas, M., Milligan, T., Villamar, M. F., Hoch, D., Purves, S., Esmaeili, B., Stanley, M., Lehn-Schioler, T., Tellez-Zenteno, J., Gonzalez-Giraldo, E., Tolokh, I., Heidarian, L., Worden, L., Jadeja, N., Fridinger, S., Lee, L., Law, E., Fodé Abass, C., Mateen, F. J.

32. Trusted AI and the Contribution of Trust Modeling in Multiagent Systems
    AAMAS (2019)
    Cohen, R., Schaekermann, M., Liu, S., & Cormier, M.

33. Capturing Expert Arguments from Medical Adjudication Discussions in a Machine-readable Format
    WWW Workshop (2019)
    Schaekermann, M., Beaton, G., Habib, M., Lim, A., Larson, K., & Law, E.
    [First Author]

34. crowdEEG: A Platform for Structured Consensus Formation in Medical Time Series Analysis
    CHI Workshop (2019)
    Schaekermann, M., Beaton, G., Habib, M., Lim, A., Larson, K., & Law, E.
    [First Author]

35. Utilizing a wearable smartphone-based EEG for pediatric epilepsy patients in the resource poor environment of Guinea: A prospective study
    Neurology (2019)
    Williams, J., Cisse, F. A., Schaekermann, M., Sakadi, F., Tassiou, N. R., BAH, A. K., Hamani, A. B. D., Lim, A., Leung, E. C. W., Fantaneau, T. A., Milligan, T., Khatri, V., Hoch, D., Vyas, M., Lam, A., Hotan, G., Cohen, J., Law, E., & Mateen, F.

36. Smartphone EEG and remote online interpretation for children with epilepsy in the Republic of Guinea: Quality, characteristics, and practice implications Seizure (2019)
    Williams, J. A., Cisse, F. A., Schaekermann, M., Sakadi, F., Tassiou, N. R., Hotan, G. C., Bah, A. K., Hamani, A. B. D., Lim, A., Leung, E. C. W., Fantaneanu, T. A., Milligan, T. A., Khatri, V., Hoch, D. B., Vyas, M. v., Lam, A. D., Cohen, J. M., Vogel, A. C., Law, E., & Mateen, F. J.

37. Asynchronous Remote Adjudication for Grading Diabetic Retinopathy
    Investigative Ophthalmology & Visual Science (2019)
    Schaekermann, M., Hammel, N., Basham, B., Campana, B., Law, E., Peng, L., Webster, D. R., & Sayres, R.
    [First Author]

38. Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs
    Ophthalmology (2019)
    Phene, S., Dunn, R. C., Hammel, N., Liu, Y., Krause, J., Kitade, N., Schaekermann, M., Sayres, R., Wu, D. J., Bora, A., Semturs, C., Misra, A., Huang, A. E., Spitze, A., Medeiros, F. A., Maa, A. Y., Gandhi, M., Corrado, G. S., Peng, L., & Webster, D. R.

39. A Study of Feature-based Consensus Formation for Glaucoma Risk Assessment
    Investigative Ophthalmology & Visual Science (2019)
    Hammel, N., Schaekermann, M., Phene, S., Dunn, C., Peng, L., Webster, D. R., & Sayres, R.

40. Remote Tool-Based Adjudication for Grading Diabetic Retinopathy
    Translational Vision Science & Technology (2019)
    Schaekermann, M., Hammel, N., Terry, M., Ali, T. K., Liu, Y., Basham, B., Campana, B., Chen, W., Ji, X., Krause, J., Corrado, G. S., Peng, L., Webster, D. R., Law, E., & Sayres, R.
    [First Author]

41. Understanding Expert Disagreement in Medical Data Analysis through Structured Adjudication
    CSCW (2019)
    Schaekermann, M., Beaton, G., Habib, M., Lim, A., Larson, K., & Law, E.
    [First Author]

42. Expert Disagreement in Sequential Labeling: A Case Study on Adjudication in Medical Time Series Analysis
    HCOMP Workshop (2018)
    Schaekermann, M., Law, E., Larson, K., & Lim, A.
    [First Author]

43. Resolvable vs. Irresolvable Disagreement: A Study on Worker Deliberation in Crowd Work
    CSCW (2018)
    Schaekermann, M., Goh, J., Larson, K., & Law, E.
    [First Author]
    [Best Paper Award]

44. Testing Incremental Difficulty Design in Platformer Games
    CHI (2017)
    Wehbe, R. R., Mekler, E. D., Schaekermann, M., Lank, E., & Nacke, L. E.

45. Curiously Motivated: Profiling Curiosity with Self-Reports and Behaviour Metrics in the Game “Destiny”
    CHI PLAY (2017)
    Schaekermann, M., Ribeiro, G., Wallner, G., Kriglstein, S., Johnson, D., Drachen, A., Sifa, R., & Nacke, L. E.
    [First Author]

46. The Big Picture: Preserving Context in the Decomposition of Complex Expert Tasks
    CHI Workshop (2016)
    Williams, A. C., Bradshaw, J., Schaekermann, M., Tse, T., Callaghan, W., & Law, E.

47. Resolvable vs. Irresolvable Ambiguity: A New Hybrid Framework for Dealing with Uncertain Ground Truth.
    CHI Workshop (2016)
    Schaekermann, M., Law, E., Williams, A. C., & Callaghan, W.
    [First Author]

48. Implementation of a Collaborative Web Application for Annotating Gameplay Videos Based on Biometric Player Data.
    Bachelor's Thesis, University of Applied Sciences Salzburg, Austria (2014)
    Schaekermann, M.