Alan Karthikesalingam

Large language models encode clinical knowledge

2023 · 2.739 Zit. · Nature

Key challenges for delivering clinical impact with artificial intelligence

2019 · 2.220 Zit. · BMC Medicine

Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis

2021 · 818 Zit. · npj Digital Medicine

Metrics reloaded: recommendations for image analysis validation

2024 · 347 Zit. · Nature Methods

Towards Expert-Level Medical Question Answering with Large Language Models

2023 · 332 Zit. · arXiv (Cornell University)

Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol

2021 · 286 Zit. · BMJ Open

Large Language Models Encode Clinical Knowledge

2022 · 256 Zit. · arXiv (Cornell University)

Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group

2020 · 246 Zit. · Nature Medicine

A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI

2021 · 217 Zit. · Nature Medicine

Towards Conversational Diagnostic AI

2024 · 100 Zit. · arXiv (Cornell University)

Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians

2023 · 99 Zit. · Nature Medicine

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

2024 · 88 Zit. · The Lancet Digital Health

Tackling bias in AI health datasets through the STANDING Together initiative

2022 · 78 Zit. · Nature Medicine

Detecting shortcut learning for fair medical AI using shortcut testing

2023 · 73 Zit. · Nature Communications

Towards Accurate Differential Diagnosis with Large Language Models

2023 · 62 Zit. · arXiv (Cornell University)