Mike Schaekermann
Mike Schaekermann
Computer Science PhD, Eng BSc, Medicine State Exam I
Verified email at - Homepage
Cited by
Cited by
Towards expert-level medical question answering with large language models
K Singhal, T Tu, J Gottweis, R Sayres, E Wulczyn, L Hou, K Clark, S Pfohl, ...
arXiv preprint arXiv:2305.09617, 2023
Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs
S Phene, RC Dunn, N Hammel, Y Liu, J Krause, N Kitade, ...
Ophthalmology 126 (12), 1627-1639, 2019
Towards generalist biomedical ai
T Tu, S Azizi, D Driess, M Schaekermann, M Amin, PC Chang, A Carroll, ...
NEJM AI 1 (3), AIoa2300138, 2024
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study
P Ruamviboonsuk, R Tiwari, R Sayres, V Nganthavee, K Hemarat, ...
The Lancet Digital Health 4 (4), e235-e244, 2022
Resolvable vs. Irresolvable Disagreement: A Study on Worker Deliberation in Crowd Work
M Schaekermann, J Goh, K Larson, E Law
2018 ACM Conference on Computer Supported Cooperative Work and Social …, 2018
Towards conversational diagnostic ai
T Tu, A Palepu, M Schaekermann, K Saab, J Freyberg, R Tanno, A Wang, ...
arXiv preprint arXiv:2401.05654, 2024
Ambiguity-aware ai assistants for medical data analysis
M Schaekermann, G Beaton, E Sanoubari, A Lim, K Larson, E Law
Proceedings of the 2020 CHI conference on human factors in computing systems …, 2020
Understanding expert disagreement in medical data analysis through structured adjudication
M Schaekermann, G Beaton, M Habib, A Lim, K Larson, E Law
Proceedings of the ACM on Human-Computer Interaction 3 (CSCW), 1-23, 2019
Data excellence for AI: why should you care?
L Aroyo, M Lease, P Paritosh, M Schaekermann
Interactions 29 (2), 66-69, 2022
Expert discussions improve comprehension of difficult cases in medical image assessment
M Schaekermann, CJ Cai, AE Huang, R Sayres
Proceedings of the 2020 CHI conference on human factors in computing systems …, 2020
Trusted AI and the contribution of trust modeling in multiagent systems
R Cohen, M Schaekermann, S Liu, M Cormier
Proceedings of the 18th international conference on autonomous agents and …, 2019
Testing incremental difficulty design in platformer games
RR Wehbe, ED Mekler, M Schaekermann, E Lank, LE Nacke
Proceedings of the 2017 CHI conference on human factors in computing systems …, 2017
Smartphone EEG and remote online interpretation for children with epilepsy in the Republic of Guinea: Quality, characteristics, and practice implications
JA Williams, FA Cisse, M Schaekermann, F Sakadi, NR Tassiou, ...
Seizure 71, 93-99, 2019
Online Bayesian transfer learning for sequential data modeling
P Jaini, Z Chen, P Carbajal, E Law, L Middleton, K Regan, ...
International Conference on Learning Representations, 2022
Curiously motivated: profiling curiosity with self-reports and behaviour metrics in the game" destiny"
M Schaekermann, G Ribeiro, G Wallner, S Kriglstein, D Johnson, ...
Proceedings of the annual symposium on computer-human interaction in play …, 2017
Towards accurate differential diagnosis with large language models
D McDuff, M Schaekermann, T Tu, A Palepu, A Wang, J Garrison, ...
arXiv preprint arXiv:2312.00164, 2023
The challenge of variable effort crowdsourcing and how visible gold can help
D Hettiachchi, M Schaekermann, TJ McKinney, M Lease
Proceedings of the ACM on Human-Computer Interaction 5 (CSCW2), 1-26, 2021
Capabilities of gemini models in medicine
K Saab, T Tu, WH Weng, R Tanno, D Stutz, E Wulczyn, F Zhang, ...
arXiv preprint arXiv:2404.18416, 2024
Resolvable vs. Irresolvable Ambiguity: A New Hybrid Framework for Dealing with Uncertain Ground Truth
M Schaekermann, E Law, AC Williams, W Callaghan
Workshop on Human-Centered Machine Learning at CHI'16, 2016
Remote tool-based adjudication for grading diabetic retinopathy
M Schaekermann, N Hammel, M Terry, TK Ali, Y Liu, B Basham, ...
Translational Vision Science & Technology 8 (6), 40-40, 2019
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