Analysis of the constraints of artificial intelligence on the development of healthcare in primary hospitals
Objective To explore how potential artificial intelligence(AI)bias affects primary health care,and how inequities can be identified and mitigated to ensure primary healthcare development.Methods In combination with the current situation of primary health services,we investigated the bias in the whole lifetime(WLT)of AI algorithm model comprehensively and the constraint factors for the development,and put forward countermeasures.Results AI may exacerbate challenges to healthcare development in primary hospitals through-out the WLT from the proposal of research directions,data collection,variable selection,design and development to clinical practice.Hospital administrators could take countermeasures to reduce inequalities and realize AI-ena-bled primary care improvement,including strengthening their own learning capacity and top-level guidance,en-hancing medical records quality assessment,enhancing informalization construction in primary hospitals,strengthe-ning data supervision,quality control and standardization,and develop policies to introduce and cultivate talents.Conclusions The bias of AI algorithmic models throughout WLT cannot be ignored.The potential bias need to be addressed to promote equity in medical decision making in primary hospitals.In the field of public health,the reg-ulatory framework for the ethical challenges to the equity in medical outcomes by AI has not been adequately ad-dressed,which requires further attention.
Artificial intelligenceMachine learningWhole lifetimePrimary hospitalEquity in medi-cal outcomesConstraint factorCountermeasure
国家科技期刊平台
NSTL
万方数据
