XGBoost and random forest reached F1 scores of 0.87 internal and 0.83 external while GPT-4 scored 0.43 and fine-tuned Mistral reached 0.74 on COVID-19 mortality prediction from 9,134 patient records.
PLUG AND PLAY LANGUAGE MODELS: A SIMPLE APPROACH TO CONTROLLED TEXT GENERATION
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Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data
XGBoost and random forest reached F1 scores of 0.87 internal and 0.83 external while GPT-4 scored 0.43 and fine-tuned Mistral reached 0.74 on COVID-19 mortality prediction from 9,134 patient records.