Mike Schaekermann

Orcid: 0000-0002-1735-9680

According to our database1, Mike Schaekermann authored at least 30 papers between 2017 and 2024.

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Bibliography

2024
Towards Democratization of Subspeciality Medical Expertise.
CoRR, 2024

Capabilities of Gemini Models in Medicine.
CoRR, 2024

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models.
CoRR, 2024

MINT: A wrapper to make multi-modal and multi-image AI models interactive.
CoRR, 2024

Towards Conversational Diagnostic AI.
CoRR, 2024

Conversational AI in health: Design considerations from a Wizard-of-Oz dermatology case study with users, clinicians and a medical LLM.
Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024

2023
Towards Accurate Differential Diagnosis with Large Language Models.
CoRR, 2023

Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation.
CoRR, 2023

Towards Generalist Biomedical AI.
CoRR, 2023

Evaluating AI systems under uncertain ground truth: a case study in dermatology.
CoRR, 2023

Towards Expert-Level Medical Question Answering with Large Language Models.
CoRR, 2023

2022
Data excellence for AI: why should you care?
Interactions, 2022

In Search of Ambiguity: A Three-Stage Workflow Design to Clarify Annotation Guidelines for Crowd Workers.
Frontiers Artif. Intell., 2022

2021
The Challenge of Variable Effort Crowdsourcing and How Visible Gold Can Help.
Proc. ACM Hum. Comput. Interact., 2021

Proceedings of the CSCW 2021 Workshop - Investigating and Mitigating Biases in Crowdsourced Data.
CoRR, 2021

Investigating and Mitigating Biases in Crowdsourced Data.
Proceedings of the Companion Publication of the 2021 ACM Conference on Computer Supported Cooperative Work and Social Computing, 2021

2020
Human-AI Interaction in the Presence of Ambiguity: From Deliberation-based Labeling to Ambiguity-aware AI.
PhD thesis, 2020

The AI Bookie - Place Your Bets: Will Machine Learning Outgrow Human Labeling?
AI Mag., 2020

Expert Discussions Improve Comprehension of Difficult Cases in Medical Image Assessment.
Proceedings of the CHI '20: CHI Conference on Human Factors in Computing Systems, 2020

Ambiguity-aware AI Assistants for Medical Data Analysis.
Proceedings of the CHI '20: CHI Conference on Human Factors in Computing Systems, 2020

2019
Understanding Expert Disagreement in Medical Data Analysis through Structured Adjudication.
Proc. ACM Hum. Comput. Interact., 2019

Capturing Expert Arguments from Medical Adjudication Discussions in a Machine-readable Format.
Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

Trusted AI and the Contribution of Trust Modeling in Multiagent Systems.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
Resolvable vs. Irresolvable Disagreement: A Study on Worker Deliberation in Crowd Work.
Proc. ACM Hum. Comput. Interact., 2018

Deep Learning to Assess Glaucoma Risk and Associated Features in Fundus Images.
CoRR, 2018

Expert Disagreement in Sequential Labeling: A Case Study on Adjudication in Medical Time Series Analysis.
Proceedings of the 1st Workshop on Subjectivity, 2018

2017
Online Bayesian Transfer Learning for Sequential Data Modeling.
Proceedings of the 5th International Conference on Learning Representations, 2017

Curiously Motivated: Profiling Curiosity with Self-Reports and Behaviour Metrics in the Game "Destiny".
Proceedings of the Annual Symposium on Computer-Human Interaction in Play, 2017

Testing Incremental Difficulty Design in Platformer Games.
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017

Designing for Curiosity: An Interdisciplinary Workshop.
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017


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