معرفی
Peder Andersson is an affiliated researcher at Lund University's Division of Clinical Chemistry and Pharmacology, part of the Faculty of Medicine. He also serves as a teaching staff member in the Medical Programme's Mathematical Statistics section. His research focuses on predictive modeling in intensive care medicine, particularly around ICU prognostication, cardiac arrest outcomes, and biomarker-driven mortality prediction. He holds an ORCID identifier (0000-0001-8261-9613).
His work emphasizes artificial neural networks for clinical prediction systems and improving risk stratification in critical care settings. Notable projects include register-based studies on ICU patient outcomes and validation of machine learning algorithms for neurological prognosis after cardiac arrest.
Collaborations span multiple institutions, with active research networks involving co-authors from Sweden and Denmark. His research has garnered significant readership on platforms like Mendeley, with over 150 readers for his 2019 cohort study.
