Guideline‐augmented prompting improves comparative preference and response consistency of large language model outputs for orthopaedic anaesthesia questions: A controlled prompting study
Anita Széll, Yinan Yu, Jacob F. Oeding, Felix C. Oettl, Adam Piasecki, Keti Dalla, Tobias Siöland, Mathias Hård af Segerstad, Fredrik Olsen, Peter Larsson, Stefano Zaffagnini, Kristian Samuelsson, Fredrik Hessulf
ICURE: Intensive care unit (ICU) risk evaluation for 30-day mortality. Developing and evaluating a multivariable machine learning prediction model for patients admitted to the general ICU in Sweden
Tobias Siöland, Araz Rawshani, Bengt Nellgård, Johan Malmgren, Jonatan Oras, Keti Dalla, Giovanni Cinà, Lars Engerström, Fredrik Hessulf
Prediction of neurologic outcome after out-of-hospital cardiac arrest: An interpretable approach with machine learning
Araz Rawshani, Fredrik Hessulf, John Deminger, Pedram Sultanian, Vibha Gupta, Peter Lundgren, Mohammed Mohammed, Monér Abu Alchay, Tobias Siöland, Emilia Gryska, Adam Piasecki
Predicting survival and neurological outcome in out-of-hospital cardiac arrest using machine learning: the SCARS model
Fredrik Hessulf, Deepak L Bhatt, Johan Engdahl, Peter Lundgren, Elmir Omerovic, Aidin Rawshani, Edvin Helleryd, Christian Dworeck, Hans Friberg, Björn Redfors, Niklas Nielsen, Anna Myredal, Attila Frigyesi, Johan Herlitz, Araz Rawshani