Matthieu Komorowski

The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care

2018 · 1.197 Zit. · Nature Medicine

Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies

2020 · 1.032 Zit. · BMJ

Guidelines for reinforcement learning in healthcare

2018 · 364 Zit. · Nature Medicine

Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities

2020 · 114 Zit. · Frontiers in Big Data

Artificial intelligence in intensive care: are we there yet?

2019 · 57 Zit. · Intensive Care Medicine

Bridging the Health Data Divide

2016 · 54 Zit. · Journal of Medical Internet Research

Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22

2025 · 46 Zit. · Critical Care

Clinical management of sepsis can be improved by artificial intelligence: yes

2019 · 44 Zit. · Intensive Care Medicine

Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning.

2018 · 34 Zit. · PubMed

Assuring the safety of AI-based clinical decision support systems: a case study of the AI Clinician for sepsis treatment

2022 · 32 Zit. · BMJ Health & Care Informatics

Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies in medical imaging.

2020 · 31 Zit.

How could ChatGPT impact my practice as an intensivist? An overview of potential applications, risks and limitations

2023 · 29 Zit. · Intensive Care Medicine

The future of artificial intelligence in intensive care: moving from predictive to actionable AI

2023 · 28 Zit. · Intensive Care Medicine

Causal inference using observational intensive care unit data: a scoping review and recommendations for future practice

2023 · 25 Zit. · npj Digital Medicine

Eye tracking insights into physician behaviour with safe and unsafe explainable AI recommendations

2024 · 18 Zit. · npj Digital Medicine