A global log for medical AI Article Swipe
Ayush Noori
,
Adam Rodman
,
Alan Karthikesalingam
,
Bilal A. Mateen
,
Chris Longhurst
,
Daniel X. Yang
,
Dave deBronkart
,
Gauden Galea
,
Harold W. Wolf
,
Jacob Waxman
,
Joshua C. Mandel
,
Juliana Rotich
,
Kenneth D. Mandl
,
Maria Mustafa
,
Melissa Miles
,
Nigam H. Shah
,
Peter Lee
,
Robert Korom
,
Suzanne M. Mahoney
,
Seth Hain
,
Sandra E. Staffieri
,
Trevor Mundel
,
Vivek Natarajan
,
Noa Dagan
,
David A. Clifton
,
Ran D. Balicer
,
Isaac S. Kohane
,
Marinka Žitnik
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2510.04033
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2510.04033
Modern computer systems often rely on syslog, a simple, universal protocol that records every critical event across heterogeneous infrastructure. However, healthcare's rapidly growing clinical AI stack has no equivalent. As hospitals rush to pilot large language models and other AI-based clinical decision support tools, we still lack a standard way to record how, when, by whom, and for whom these AI models are used. Without that transparency and visibility, it is challenging to measure real-world performance and outcomes, detect adverse events, or correct bias or dataset drift. In the spirit of syslog, we introduce MedLog, a protocol for event-level logging of clinical AI. Any time an AI model is invoked to interact with a human, interface with another algorithm, or act independently, a MedLog record is created. This record consists of nine core fields: header, model, user, target, inputs, artifacts, outputs, outcomes, and feedback, providing a structured and consistent record of model activity. To encourage early adoption, especially in low-resource settings, and minimize the data footprint, MedLog supports risk-based sampling, lifecycle-aware retention policies, and write-behind caching; detailed traces for complex, agentic, or multi-stage workflows can also be captured under MedLog. MedLog can catalyze the development of new databases and software to store and analyze MedLog records. Realizing this vision would enable continuous surveillance, auditing, and iterative improvement of medical AI, laying the foundation for a new form of digital epidemiology.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2510.04033
- https://arxiv.org/pdf/2510.04033
- OA Status
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4414970982Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2510.04033Digital Object Identifier
- Title
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A global log for medical AIWork title
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preprintOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-10-05Full publication date if available
- Authors
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Ayush Noori, Adam Rodman, Alan Karthikesalingam, Bilal A. Mateen, Chris Longhurst, Daniel X. Yang, Dave deBronkart, Gauden Galea, Harold W. Wolf, Jacob Waxman, Joshua C. Mandel, Juliana Rotich, Kenneth D. Mandl, Maria Mustafa, Melissa Miles, Nigam H. Shah, Peter Lee, Robert Korom, Suzanne M. Mahoney, Seth Hain, Sandra E. Staffieri, Trevor Mundel, Vivek Natarajan, Noa Dagan, David A. Clifton, Ran D. Balicer, Isaac S. Kohane, Marinka ŽitnikList of authors in order
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https://arxiv.org/abs/2510.04033Publisher landing page
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https://arxiv.org/pdf/2510.04033Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2510.04033Direct OA link when available
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0Total citation count in OpenAlex
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| abstract_inverted_index.across | 16 |
| abstract_inverted_index.detect | 78 |
| abstract_inverted_index.drift. | 86 |
| abstract_inverted_index.enable | 210 |
| abstract_inverted_index.human, | 114 |
| abstract_inverted_index.laying | 220 |
| abstract_inverted_index.model, | 135 |
| abstract_inverted_index.models | 36, 61 |
| abstract_inverted_index.record | 51, 124, 128, 149 |
| abstract_inverted_index.spirit | 89 |
| abstract_inverted_index.tools, | 43 |
| abstract_inverted_index.traces | 177 |
| abstract_inverted_index.vision | 208 |
| abstract_inverted_index.MedLog, | 94 |
| abstract_inverted_index.MedLog. | 189 |
| abstract_inverted_index.Without | 64 |
| abstract_inverted_index.adverse | 79 |
| abstract_inverted_index.analyze | 203 |
| abstract_inverted_index.another | 117 |
| abstract_inverted_index.correct | 82 |
| abstract_inverted_index.dataset | 85 |
| abstract_inverted_index.digital | 228 |
| abstract_inverted_index.events, | 80 |
| abstract_inverted_index.fields: | 133 |
| abstract_inverted_index.growing | 22 |
| abstract_inverted_index.header, | 134 |
| abstract_inverted_index.inputs, | 138 |
| abstract_inverted_index.invoked | 109 |
| abstract_inverted_index.logging | 99 |
| abstract_inverted_index.measure | 73 |
| abstract_inverted_index.medical | 218 |
| abstract_inverted_index.rapidly | 21 |
| abstract_inverted_index.records | 12 |
| abstract_inverted_index.simple, | 8 |
| abstract_inverted_index.support | 42 |
| abstract_inverted_index.syslog, | 6, 91 |
| abstract_inverted_index.systems | 2 |
| abstract_inverted_index.target, | 137 |
| abstract_inverted_index.AI-based | 39 |
| abstract_inverted_index.However, | 19 |
| abstract_inverted_index.agentic, | 180 |
| abstract_inverted_index.caching; | 175 |
| abstract_inverted_index.captured | 187 |
| abstract_inverted_index.catalyze | 192 |
| abstract_inverted_index.clinical | 23, 40, 101 |
| abstract_inverted_index.complex, | 179 |
| abstract_inverted_index.computer | 1 |
| abstract_inverted_index.consists | 129 |
| abstract_inverted_index.created. | 126 |
| abstract_inverted_index.critical | 14 |
| abstract_inverted_index.decision | 41 |
| abstract_inverted_index.detailed | 176 |
| abstract_inverted_index.interact | 111 |
| abstract_inverted_index.language | 35 |
| abstract_inverted_index.minimize | 162 |
| abstract_inverted_index.outputs, | 140 |
| abstract_inverted_index.protocol | 10, 96 |
| abstract_inverted_index.records. | 205 |
| abstract_inverted_index.software | 199 |
| abstract_inverted_index.standard | 48 |
| abstract_inverted_index.supports | 167 |
| abstract_inverted_index.Realizing | 206 |
| abstract_inverted_index.activity. | 152 |
| abstract_inverted_index.adoption, | 156 |
| abstract_inverted_index.auditing, | 213 |
| abstract_inverted_index.databases | 197 |
| abstract_inverted_index.encourage | 154 |
| abstract_inverted_index.feedback, | 143 |
| abstract_inverted_index.hospitals | 30 |
| abstract_inverted_index.interface | 115 |
| abstract_inverted_index.introduce | 93 |
| abstract_inverted_index.iterative | 215 |
| abstract_inverted_index.outcomes, | 77, 141 |
| abstract_inverted_index.policies, | 172 |
| abstract_inverted_index.providing | 144 |
| abstract_inverted_index.retention | 171 |
| abstract_inverted_index.sampling, | 169 |
| abstract_inverted_index.settings, | 160 |
| abstract_inverted_index.universal | 9 |
| abstract_inverted_index.workflows | 183 |
| abstract_inverted_index.algorithm, | 118 |
| abstract_inverted_index.artifacts, | 139 |
| abstract_inverted_index.consistent | 148 |
| abstract_inverted_index.continuous | 211 |
| abstract_inverted_index.especially | 157 |
| abstract_inverted_index.footprint, | 165 |
| abstract_inverted_index.foundation | 222 |
| abstract_inverted_index.real-world | 74 |
| abstract_inverted_index.risk-based | 168 |
| abstract_inverted_index.structured | 146 |
| abstract_inverted_index.challenging | 71 |
| abstract_inverted_index.development | 194 |
| abstract_inverted_index.equivalent. | 28 |
| abstract_inverted_index.event-level | 98 |
| abstract_inverted_index.improvement | 216 |
| abstract_inverted_index.multi-stage | 182 |
| abstract_inverted_index.performance | 75 |
| abstract_inverted_index.visibility, | 68 |
| abstract_inverted_index.healthcare's | 20 |
| abstract_inverted_index.low-resource | 159 |
| abstract_inverted_index.transparency | 66 |
| abstract_inverted_index.write-behind | 174 |
| abstract_inverted_index.epidemiology. | 229 |
| abstract_inverted_index.heterogeneous | 17 |
| abstract_inverted_index.surveillance, | 212 |
| abstract_inverted_index.independently, | 121 |
| abstract_inverted_index.infrastructure. | 18 |
| abstract_inverted_index.lifecycle-aware | 170 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 28 |
| citation_normalized_percentile |