Research graph
References from Routine laboratory panels classify internal medicine <i>ICD-10</i> code groups: comparison with frontier large language models and laboratory-only specialist assessment. Local targets link to admitted publications; unresolved targets remain external evidence.
Machine learning in health care and laboratory medicine: general overview of supervised learning and Auto-ML
10.1111/ijlh.13537 · 2021 · External reference
Artificial intelligence and mapping a new direction in laboratory medicine: a review
10.1093/clinchem/hvab165 · 2021 · External reference
Clinical chemistry in higher dimensions: machine-learning and enhanced prediction from routine clinical chemistry data
10.1016/j.clinbiochem.2016.07.013 · 2016 · External reference
Artificial intelligence models for predicting iron deficiency anemia and iron serum level based on accessible laboratory data
10.1007/s10916-011-9668-3 · 2012 · External reference
Predicting the early risk of chronic kidney disease in patients with diabetes using real-world data
10.1038/s41591-018-0239-8 · 2019 · External reference
The prevalence and mortality of hyponatremia is seriously underestimated in Chinese general medical patients
10.1186/s12882-017-0744-x · 2017 · External reference
Early detection of sepsis with machine learning techniques: a brief clinical perspective
10.3389/fmed.2021.617486 · 2021 · External reference
An application of machine learning to hematological diagnosis
10.1038/s41598-017-18564-8 · 2018 · External reference
Explainability for artificial intelligence in healthcare: a multidisciplinary perspective
10.1186/s12911-020-01332-6 · 2020 · External reference
Large language models encode clinical knowledge
10.1038/s41586-023-06291-2 · 2023 · External reference
Accuracy of a generative artificial intelligence model in a complex diagnostic challenge
10.1001/jama.2023.8288 · 2023 · External reference
Large language model influence on diagnostic reasoning: a randomized clinical trial
10.1001/jamanetworkopen.2024.40969 · 2024 · External reference
Preliminary analysis of the impact of lab results on large language model generated differential diagnoses
10.1038/s41746-025-01556-8 · 2025 · External reference
Evaluation of the performance of Advanced Large Language Models in laboratory medicine using residency examinations
10.3343/alm.2025.0200 · 2026 · External reference
Comparative analysis of large language models in clinical diagnosis: performance evaluation across common and complex medical cases
10.1093/jamiaopen/ooaf055 · 2025 · External reference
Unresolved reference
2022 · External reference
Tabular data: deep learning is not all you need
10.1016/j.inffus.2021.11.011 · 2022 · External reference
Decision curve analysis: a novel method for evaluating prediction models
10.1177/0272989x06295361 · 2006 · External reference
Revisiting deep learning models for tabular data
2021 · External reference
Accurate predictions on small data with a tabular foundation model
10.1038/s41586-024-08328-6 · 2025 · External reference
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
10.1136/bmj-2023-078378 · 2024 · External reference
