Method for predicting depression occurrence using artificial intelligence model and computer readable record medium thereof

• Main Authors: HWANG SANG WON, URTNASANERDENEBAYAR, LEE JIN HEE
• Format: Patent
• Language: English; Korean
• Published: 13.12.2022
• Subjects: DIAGNOSIS; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; HUMAN NECESSITIES; HYGIENE; IDENTIFICATION; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; MEDICAL OR VETERINARY SCIENCE; PHYSICS; SURGERY

The present invention relates to a method for predicting the depression occurrence using an artificial intelligence model. The method of the present invention may include: a data receiving step in which a processor of a computing device receives big data including biological data, psychological data, and sociological data from a server connected to the device; a first parameter extraction step in which a processor extracts a parameter related to the occurrence of depression from the received data; and a depression occurrence prediction step of predicting the depression occurrence through a result value obtained by inputting the extracted first parameter into the learned artificial intelligence model. 본 발명은 인공지능 모델을 이용한 우울증 발생 예측방법에 관한 것이다. 본 방법은 컴퓨팅 장치의 프로세서가 상기 장치와 연결된 서버로부터 생물학적 데이터, 심리학적 데이터 및 사회학적 데이터가 포함된 빅데이터를 수신받는 데이터 수신단계, 프로세서가 수신받은 데이터들 중 우울증 발생과 관련된 파라미터를 추출하는 제1 파라미터 추출단계 및 추출된 제1 파라미터를 학습된 인공지능 모델에 입력하여 나온 결과값을 통해 우울증 발생을 예측하는 우울증 발생 예측단계를 포함할 수 있다.