Schaekermann, Mike
Google (United States)
17 papers on CoChatORCID 0000-0002-1735-9680
Most cited papers
- Verified
Toward expert-level medical question answering with large language models
Singhal, K., Tu, T., Gottweis, J., Sayres, R., Wulczyn, E., Amin, M., Hou, L., Clark, K., Pfohl, S. R., Cole-Lewis, H., et al. (2025) · Nature Medicine
Artificial Intelligence in Healthcare and EducationTopic Modeling
Cited by 1,734
- Verified
Towards Generalist Biomedical AI
Tu, T., Azizi, S., Driess, D., Schaekermann, M., Amin, M., Chang, P.-C., Carroll, A., Lau, C., Tanno, R., Ktena, I., et al. (2023) · arXiv
Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications
Cited by 483
- Verified
Towards Generalist Biomedical AI
Tu, T., Azizi, S., Driess, D., Schaekermann, M., Amin, M., Chang, P.-C., Carroll, A., Lau, C., Tanno, R., Ktena, I., et al. (2024) · NEJM AI
Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications
Cited by 483
- Verified
Towards conversational diagnostic artificial intelligence
Tu, T., Schaekermann, M., Palepu, A., Saab, K., Freyberg, J., Tanno, R., Wang, A., Li, B., Amin, M., Cheng, Y., et al. (2025) · Nature
Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare
Cited by 366
- Verified
Towards Expert-Level Medical Question Answering with Large Language Models
Singhal, K., Tu, T., Gottweis, J., Sayres, R., Wulczyn, E., Hou, L., Clark, K., Pfohl, S., Cole-Lewis, H., Neal, D., et al. (2023) · arXiv
Artificial Intelligence in Healthcare and EducationTopic Modeling
Cited by 338
- Verified
Towards accurate differential diagnosis with large language models
McDuff, D., Schaekermann, M., Tu, T., Palepu, A., Wang, A., Garrison, J., Singhal, K., Sharma, Y., Azizi, S., Kulkarni, K., et al. (2025) · Nature
Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare
Cited by 311
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Towards Accurate Differential Diagnosis with Large Language Models
McDuff, D., Schaekermann, M., Tu, T., Palepu, A., Wang, A., Garrison, J., Singhal, K., Sharma, Y., Azizi, S., Kulkarni, K., et al. (2023) · arXiv
Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare
Cited by 311
- Verified
Collaboration between clinicians and vision–language models in radiology report generation
Tanno, R., Barrett, D. G. T., Sellergren, A., Ghaisas, S., Dathathri, S., See, A., Welbl, J., Lau, C., Tu, T., Azizi, S., et al. (2025) · Nature Medicine
Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications
Cited by 186
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Deep Learning and Glaucoma Specialists
Phene, S., Dunn, R. C., Hammel, N., Liu, Y., Krause, J., Kitade, N., Schaekermann, M., Sayres, R., Wu, D. J., Bora, A., et al. (2019) · Ophthalmology
Retinal Imaging and AnalysisGlaucoma and retinal disorders
Cited by 186
- Verified
Capabilities of Gemini Models in Medicine
Saab, K., Tu, T., Weng, W.-H., Tanno, R., Stutz, D., Wulczyn, E., Zhang, F., Strother, T., Park, C., Vedadi, E., et al. (2024) · arXiv
Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications
Cited by 117
- Verified
A toolbox for surfacing health equity harms and biases in large language models
Pfohl, S. R., Cole-Lewis, H., Sayres, R., Neal, D., Asiedu, M., Dieng, A., Tomasev, N., Rashid, Q. M., Azizi, S., Rostamzadeh, N., et al. (2024) · Nature Medicine
Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education
Cited by 113
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Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 69
- Verified
Data excellence for AI: why should you care?
Aroyo, L., Lease, M., Paritosh, P., & Schaekermann, M. (2022) · Interactions
Innovative Human-Technology InteractionEthics and Social Impacts of AI
Cited by 31
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Expert Discussions Improve Comprehension of Difficult Cases in Medical Image Assessment
Schaekermann, M., Cai, C. J., Huang, A. E., & Sayres, R. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Retinal Imaging and AnalysisMachine Learning and Data Classification
Cited by 28
- Verified
Remote Tool-Based Adjudication for Grading Diabetic Retinopathy
Schaekermann, M., Hammel, N., Terry, M., Ali, T. K., Liu, Y., Basham, B., Campana, B., Chen, W., Ji, X., Krause, J., et al. (2019) · Translational Vision Science & Technology
Retinal Imaging and AnalysisRetinal Diseases and Treatments
Cited by 19
- Verified
Generative AI for medical education: Insights from a case study with medical students and an AI tutor for clinical reasoning
Wang, A., Ruparel, R., Iurchenko, A., Jhun, P., Séguin, J. A., Strachan, P., Wong, R., Karthikesalingam, A., Matias, Y., Hassidim, A., et al. (2025) · Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems
Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Education
Cited by 6
- Verified
LearnLM: Improving Gemini for Learning
LearnLM Team, Modi, A., Veerubhotla, A. S., Rysbek, A., Huber, A., Wiltshire, B., Veprek, B., Gillick, D., Kasenberg, D., Ahmed, D., et al. (2024) · arXiv
Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education
Cited by 4
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