Machine Learning Models Prognosticate Functional Outcomes Better than Clinical Scores in Spontaneous Intracerebral Haemorrhage

Spontaneous intracerebral haemorrhage (SICH) was associated with an overall incidence of 24.6 per 100,000 person-years worldwide and was most common in Asians, with an incidence of 51.8 per 100,000 person-years.1 SICH is a major cause of mortality and morbidity, with a case fatality of 40.4% at one month, one-year mortality rate of 54.0% and only 12 to 39% of patients leading an independent life on follow up.1,2 Current management for SICH remains supportive, and includes outcome prediction and rehabilitation.

Source: Journal of Stroke and Cerebrovascular Diseases - December 10, 2021 Category: Neurology Authors: Mervyn Jun Rui Lim, Raphael Hao Chong Quek, Kai Jie Ng, Ne-Hooi Will Loh, Sein Lwin, Kejia Teo, Vincent Diong Weng Nga, Tseng Tsai Yeo, Mehul Motani Source Type: research