- Using Machine Learning Models to Identify Factors Associated With 30-Day Readmissions After Posterior Cervical Fusions: A Longitudinal Cohort Study
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Gonzalez-Suarez AD, Rezaii PG, Herrick D, Tigchelaar SS, Ratliff JK, Rusu M, Scheinker D, Jeon I, Desai AM
- KMID: 2557035
- Neurospine.
- 2024 Jun;21(2):620-632.
- doi: 10.14245/ns.2347340.670
Objective: Readmission rates after posterior cervical fusion (PCF) significantly impact patients and healthcare, with complication rates at 15%–25% and up to 12% 90-day readmission rates. In this study, we aim... -
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- Analyzing Large Language Models’ Responses to Common Lumbar Spine Fusion Surgery Questions: A Comparison Between ChatGPT and Bard
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Lang SP, Yoseph ET, Gonzalez-Suarez AD, Kim R, Fatemi P, Wagner K, Maldaner N, Stienen MN, Zygourakis CC
- KMID: 2557036
- Neurospine.
- 2024 Jun;21(2):633-641.
- doi: 10.14245/ns.2448098.049
Objective: In the digital age, patients turn to online sources for lumbar spine fusion information, necessitating a careful study of large language models (LLMs) like chat generative pre-trained transformer (ChatGPT)... -
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