Weakly supervised multitask learning models to identify symptom onset time of unclear-onset intracerebral hemorrhage.

Chang JianboPei HanqiChen YihaoJiang ChengShang HongWang YuxiangWang XiaoningYe ZejuWang XingongTian FengxuanChai JianjunXu JijunLi ZhaojianMa WenbinWei JunjiJianhua YaoFeng MingRenzhi Wang

Published in: International journal of stroke : official journal of the International Stroke Society (2021)

The WS-MTL models showed good performance and generalizability. Considering the large number of unclear-onset spontaneous intracerebral hemorrhage patients, it may be worth to integrate the WS-MTL model into clinical practice to identify the onset time.

Keyphrases

end stage renal disease
clinical practice
chronic kidney disease
newly diagnosed
machine learning
patient reported