Prognostic biomarkers of intracerebral hemorrhage identified using targeted proteomics and machine learning algorithms - Misra, Shubham; Kawamura, Yuki; Singh, Praveen; Sengupta, Shantanu; Nath, Manabesh; Rahman, Zuhaibur; Kumar, Pradeep; Kumar, Amit; Aggarwal, Praveen; Srivastava, Achal K.; Pandit, Awadh K.; Mohania, Dheeraj; et al. (PloS one, 2024)
Keywords: Acids; Aged; Algorithms; Analysis; Biological markers; Biology and Life Sciences; Biomarkers; Biomarkers - blood; Cerebral Hemorrhage - blood; Cerebral Hemorrhage - diagnosis; Cerebral Hemorrhage - mortality; Computer and Information Sciences; Confidence intervals; Data mining; Female; Gelatinase A; Gelatinase B; Haptoglobin; Health aspects; Health care access; Hemorrhage; Humans; India; Insulin-like growth factor-binding protein 3; Intracerebral hemorrhage; Learning algorithms; Machine Learning; Male; Medical prognosis; Medical research; Medicine and Health Sciences; Medicine, Experimental; Middle Aged; Mortality; Peptides; Physical Sciences; Prediction models; Predictions; Prognosis; Protein gene product 9.5; Proteins; Proteomics; Proteomics - methods; Regression analysis; Regression models; Research and Analysis Methods; Statistical analysis; Stroke; Variables; α2-Macroglobulin; India