Dr Emmanuel Ogundimu's Outputs (3)

Long-term outcomes of mini-sternotomy versus conventional sternotomy for aortic valve replacement: a randomised controlled trial (2022)
Journal Article
Telyuk, P., Hancock, H., Maier, R., Batty, J. A., Goodwin, A., Owens, W. A., …Akowuah, E. (2023). Long-term outcomes of mini-sternotomy versus conventional sternotomy for aortic valve replacement: a randomised controlled trial. European Journal of Cardio-Thoracic Surgery, 63(1), Article ezac540. https://doi.org/10.1093/ejcts/ezac540

Objectives Aortic valve replacement (AVR) for severe symptomatic aortic stenosis is one of the most common cardiac surgical procedures with excellent long-term outcomes. Multiple previous studies have compared short-term outcomes of AVR with mini-ste... Read More about Long-term outcomes of mini-sternotomy versus conventional sternotomy for aortic valve replacement: a randomised controlled trial.

Managing Unusual Sensory Experiences in People with First-Episode Psychosis (MUSE FEP): a study protocol for a single-blind parallel-group randomised controlled feasibility trial (2022)
Journal Article
Dudley, R., Dodgson, G., Common, S., O'Grady, L., Watson, F., Gibbs, C., …Aynsworth, C. (2022). Managing Unusual Sensory Experiences in People with First-Episode Psychosis (MUSE FEP): a study protocol for a single-blind parallel-group randomised controlled feasibility trial. BMJ Open, 12(5), Article e061827. https://doi.org/10.1136/bmjopen-2022-061827

Introduction Hallucinations (hearing or seeing things that others do not) are a common feature of psychosis, causing significant distress and disability. Existing treatments such as cognitive–behavioural therapy for psychosis (CBTp) have modest benef... Read More about Managing Unusual Sensory Experiences in People with First-Episode Psychosis (MUSE FEP): a study protocol for a single-blind parallel-group randomised controlled feasibility trial.

On Lasso and adaptive Lasso for non-random sample in credit scoring (2022)
Journal Article
Ogundimu, E. O. (2024). On Lasso and adaptive Lasso for non-random sample in credit scoring. Statistical Modelling, 24(2), 115-138. https://doi.org/10.1177/1471082x221092181

Prediction models in credit scoring are often formulated using available data on accepted applicants at the loan application stage. The use of this data to estimate probability of default (PD) may lead to bias due to non-random selection from the pop... Read More about On Lasso and adaptive Lasso for non-random sample in credit scoring.