인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract In the current age, the mental condition of people varies rapidly due to various factors such as social relationships, eating disorders, and economic crisis. There are various factors that can be overcome, such as regular exercise, community engagement, meditation, reading books, and yoga. But there are situations where people cannot undergo the mentioned strategies. As advances in data science and big data continue, there is an increasing availability of drug review datasets. There are various manual and traditional approaches to identify the proper drug and condition with some flaws such as overtime, measurement error of the drug, and high computational complexity. Due to these barriers, cutting-edge technologies are involved in data exploration (data cleaning, data transformation, data integration, etc.) to identify the proper prescription of the condition with machine learning approaches. Furthermore, the proposed work has a threefold unique approach that includes the integration of datasets, the creation of a new dataset, and the focus on exploratory data analysis. In the final step, a novel dataset is created from multiple datasets on behavioral healthcare drug reviews that are compared with individual datasets. The main objective of the work is to satisfy the customer’s health in all aspects. The work is verified by identifying the prescription for popular health conditions such as anxiety, depression, insomnia, panic disorder, and bipolar disorder.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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