Open Access<p>Integrating Unified Medical Language System and Kleinberg’s Burst Detection Algorithm into Research Topics of Medications for Post-Traumatic Stress Disorder</p>
Author(s) -
Shuang Xu,
Dan Xu,
Liang Wen,
Chunrong Zhu,
Ying Yang,
Shuang Han,
Peng Guan
Publication year - 2020
Publication title -
drug design, development and therapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.964
H-Index - 64
ISSN - 1177-8881
DOI - 10.2147/dddt.s270379
Subject(s) - algorithm , set (abstract data type) , computer science , unified medical language system , pharmacotherapy , medicine , psychiatry , information retrieval , psychology , programming language
The treatment of post-traumatic stress disorder (PTSD) has long been a challenge because the symptoms of PTSD are multifaceted. PTSD is primarily treated with psychotherapy and medication, or a combination of psychotherapy and medication. The present study was designed to analyze the literature on medications for PTSD and explore high-frequency common drugs and low-frequency burst drugs by burst detection algorithm combined with Unified Medical Language System (UMLS) and provide references for developing new drugs for PTSD.