Causal Association Mining from Geriatric Literature

Literature pertaining to geriatric care contains rich information regarding the best practices related to geriatric health care issues. The publication domain of geriatric care is small as compared to other health related areas, however, there are over a million articles pertaining to different cases and case interventions capturing best practice outcomes. The knowledge extracted from these articles could be harvested and translated from research to practice in a quicker and more efficient manner. Geriatric literature contains multiple domains that contain information such as interventions, information on care for elderly, case studies and real life scenarios. These articles contain a variety of causal relationships such as the relationship between interventions and disorders. The goal of this study is to identify these causal relations from published abstracts. Natural language processing and statistical methods were adopted to identify and extract these causal relations with a precision of 79.54% and recall of 81%.