Revolutionizing Healthcare Data Analysis: Semi-Supervised EHR Classification with Transfer Learning
Disciplines
Computer Engineering | Other Computer Engineering
Abstract (300 words maximum)
Electronic Health Records are a vital tool in combating the increasing suicide rate among young adults in the United States through providing an insight into the patient’s current mental state. However, given the limited resources available in the mental health industry, there is a need for robust algorithms which can detect and predict suicidal behaviors. Therefore, our research plans are to develop an NLP algorithm which can traverse the dataset, detect instances of suicide attempts or ideation, and provide information regarding the type of suicide.
Academic department under which the project should be listed
CCSE - Computer Science
Primary Investigator (PI) Name
Md Abdullah Al Hafiz Khan
Revolutionizing Healthcare Data Analysis: Semi-Supervised EHR Classification with Transfer Learning
Electronic Health Records are a vital tool in combating the increasing suicide rate among young adults in the United States through providing an insight into the patient’s current mental state. However, given the limited resources available in the mental health industry, there is a need for robust algorithms which can detect and predict suicidal behaviors. Therefore, our research plans are to develop an NLP algorithm which can traverse the dataset, detect instances of suicide attempts or ideation, and provide information regarding the type of suicide.