A tutorial on calibration measurements and calibration models for clinical prediction models

Y Huang, W Li, F Macheret, RA Gabriel… - Journal of the …, 2020 - academic.oup.com
Our primary objective is to provide the clinical informatics community with an introductory
tutorial on calibration measurements and calibration models for predictive models using …

Enhanced whale optimization algorithm for medical feature selection: A COVID-19 case study

MH Nadimi-Shahraki, H Zamani, S Mirjalili - Computers in biology and …, 2022 - Elsevier
The whale optimization algorithm (WOA) is a prominent problem solver which is broadly
applied to solve NP-hard problems such as feature selection. However, it and most of its …

Interpretation and use of applied/operational machine learning and artificial intelligence in surgery

MJ Douglas, R Callcut, LA Celi… - Surgical Clinics, 2023 - surgical.theclinics.com
The work of surgeons is complex, incorporating cognitive and manual skills, analytical
processing, creativity, and navigation of nuanced personal interactions. Yet, humans have …

Predicting whether patients will achieve minimal clinically important differences following hip or knee arthroplasty: a performance comparison of machine learning …

B Langenberger, D Schrednitzki… - Bone & Joint …, 2023 - boneandjoint.org.uk
Aims A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty
(HA) do not achieve an improvement as high as the minimal clinically important difference …

Classification of imbalanced data using machine learning algorithms to predict the risk of renal graft failures in Ethiopia

G Mulugeta, T Zewotir, AS Tegegne, LH Juhar… - BMC Medical Informatics …, 2023 - Springer
Introduction The prevalence of end-stage renal disease has raised the need for renal
replacement therapy over recent decades. Even though a kidney transplant offers an …

[HTML][HTML] Developing an individualized risk calculator for psychopathology among young people victimized during childhood: A population-representative cohort study

AJ Meehan, RM Latham, L Arseneault, D Stahl… - Journal of Affective …, 2020 - Elsevier
Background Victimized children are at greater risk for psychopathology than non-victimized
peers. However, not all victimized children develop psychiatric disorders, and accurately …

Factors associated with 30-day and 1-year readmission among psychiatric inpatients in Beijing China: a retrospective, medical record-based analysis

X Han, F Jiang, Y Tang, J Needleman, M Guo, Y Chen… - BMC psychiatry, 2020 - Springer
Background Psychiatric readmissions negatively impact patients and their families while
increasing healthcare costs. This study aimed at investigating factors associated with …

[HTML][HTML] Predicting the risk of future depression among school-attending adolescents in Nigeria using a model developed in Brazil.

R Brathwaite, TBM Rocha, C Kieling, BA Kohrt… - Psychiatry …, 2020 - Elsevier
Depression commonly emerges in adolescence and is a major public health issue in low-
and middle-income countries where 90% of the world's adolescents live. Thus efforts to …

Artificial neural networks improve and simplify intensive care mortality prognostication: a national cohort study of 217,289 first-time intensive care unit admissions

G Holmgren, P Andersson, A Jakobsson… - Journal of intensive …, 2019 - Springer
Purpose We investigated if early intensive care unit (ICU) scoring with the Simplified Acute
Physiology Score (SAPS 3) could be improved using artificial neural networks (ANNs) …

Predicting the risk of depression among adolescents in Nepal using a model developed in Brazil: the IDEA Project

R Brathwaite, TBM Rocha, C Kieling, K Gautam… - European child & …, 2021 - Springer
The burden of adolescent depression is high in low-and middle-income countries (LMICs),
yet research into prevention is lacking. Development and validation of models to predict …