| 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 | 157 | 2019 |
| 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 | 99 | 2023 |
| 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 | 73 | 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 | 67 | 2018 |
| 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 | 42 | 2020 |
| Towards generalist biomedical AI T Tu, S Azizi, D Driess, M Schaekermann, M Amin, PC Chang, A Carroll, ... arXiv preprint arXiv:2307.14334, 2023 | 34 | 2023 |
| 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 | 34 | 2019 |
| Data excellence for AI: why should you care? L Aroyo, M Lease, P Paritosh, M Schaekermann Interactions 29 (2), 66-69, 2022 | 26 | 2022 |
| 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 | 26 | 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 | 26 | 2017 |
| 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 | 25 | 2020 |
| 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, 2016 | 24 | 2016 |
| 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 | 20 | 2019 |
| 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 | 19 | 2017 |
| 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 | 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 | 15 | 2019 |
| Longitudinal screening for diabetic retinopathy in a nationwide screening program: comparing deep learning and human graders J Limwattanayingyong, V Nganthavee, K Seresirikachorn, T Singalavanija, ... Journal of diabetes research 2020, 2020 | 10 | 2020 |
| 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 | 9 | 2021 |
| Expert Disagreement in Sequential Labeling: A Case Study on Adjudication in Medical Time Series Analysis. M Schaekermann, E Law, K Larson, A Lim SAD/CrowdBias@ HCOMP, 55-66, 2018 | 9 | 2018 |
| Investigating and mitigating biases in crowdsourced data D Hettiachchi, M Sanderson, J Goncalves, S Hosio, G Kazai, M Lease, ... Companion Publication of the 2021 Conference on Computer Supported …, 2021 | 7 | 2021 |
Edith LawAssociate Professor, David R. Cheriton School of Computer Science, University of WaterlooVerified email at uwaterloo.ca
