Larske M Soepnel, Shane A Norris, Khuthala Mabetha, Molebogeng Motlhatlhedi, Nokuthula Nkosi, Stephen Lye, Catherine E Draper
A qualitative analysis of community health worker perspectives on the implementation of the preconception and pregnancy phases of the Bukhali randomised controlled trial
PLOS global public health
artificial intelligence ai medicine transforming healthcare automating system tasks assisting diagnostics predicting patient outcomes personalising patient care founded ability analyse vast datasets paediatric endocrinology ai developed diabetes insulin dose adjustment detection hypoglycaemia retinopathy screening bone age assessment thyroid nodule screening identification growth disorders diagnosis precocious puberty use facial recognition algorithms conditions cushing syndrome acromegaly congenital adrenal hyperplasia turner syndrome ai also predict risk childhood obesity stratifying future interventions modify lifestyle ai facilitate personalised healthcare integrating data omics analysis lifestyle tracking medical history laboratory imaging therapy response treatment adherence multiple sources data acquisition processing becomes fundamental data privacy protecting childrens health data crucial minimising algorithmic bias generated ai analysis rare conditions seen paediatric endocrinology important determinant ai validity clinical practice ai cannot create patientdoctor relationship assess wider holistic determinants care children individual needs vulnerabilities considered context family relationships dynamics importantly whilst ai provides value augmenting efficiency accuracy must used replace clinical skills