Kayla Parsons, Kelley Strout, Caitlyn Winn, Mona Therrien-Genest, Kate Yerxa, Jade McNamara
Development of Master Chef: A Curriculum to Promote Nutrition and Mindful Eating among College Students
International journal of environmental research and public health
background artificial intelligence ai algorithms applied breast cancer risk prediction prevention using patient history scans imaging information analysis specific genes cancer classification reduce overdiagnosis overtreatment scoping review aimed identify barriers encountered applying innovative ai techniques models developing breast cancer risk prediction scores promoting screening behaviors among adult females findings may inform guide future global recommendations ai application breast cancer prevention care female populations methods prismascr preferred reporting items systematic reviews metaanalyses extension scoping reviews used reference checklist throughout study arksey omalley methodology used framework guide review framework methodology consisted five steps 1 identify research questions 2 search relevant studies 3 selection studies relevant research questions 4 chart data 5 collate summarize report results results field breast cancer risk detection prevention following ai techniques models applied machine deep learning model mldl model n 1 academic algorithms n 2 breast cancer surveillance consortium bcsc clinical 5year risk prediction model n 2 deeplearning computer vision ai algorithms n 2 aibased thermal imaging solution thermalytix n 1 realrisks n 2 breast cancer risk navigation n 1 mammorisk mlbased tool n 1 various mlmodels n 1 various machinedeep learning decision aids commercial algorithms n 7 11 included studies total 39 barriers ai applications breast cancer risk prediction screening efforts identified common barriers application innovative ai tools breast cancer prediction improved screening rates included lack external validity limited generalizability n 6 ai used studies either small sample size datasets missing data many studies n 5 also encountered selection bias due exclusion certain populations based characteristics raceethnicity family history past medical history several recommendations future research considered ai models need include broader spectrum complete predictive variables risk assessment investigating longterm outcomes improved followup periods critical assess impacts ai clinical decisions beyond immediate outcomes utilizing ai improve communication strategies local organizational level assist informed decisionmaking compliance especially populations limited literacy levels conclusions use ai patient education adjunctive tool providers still early incorporation future research explore implementation aidriven resources enhance understanding decisionmaking regarding breast cancer screening especially vulnerable populations limited literacy