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Full-Text Articles in Physical Sciences and Mathematics
Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita
Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita
Computer Science and Engineering Faculty Publications
Heart failure is a syndrome which occurs when the heart is not able to pump blood and oxygen to support other organs in the body. Identifying the underlying themes in the diagnostic codes and procedure reports of patients admitted for heart failure could reveal the clinical phenotypes associated with heart failure and to group patients based on their similar characteristics which could also help in predicting patient outcomes like length of stay. These clinical phenotypes usually have a probabilistic latent structure and hence, as there has been no previous work on identifying phenotypes in clinical notes of heart failure patients …
Leveraging Natural Learning Processing To Uncover Themes In Clinical Notes Of Patients Admitted For Heart Failure, Ankita Agarwal, Krishnaprasad Thirunarayan, William Romine, Amanuel Alambo, Mia Cajita, Tanvi Banerjee
Leveraging Natural Learning Processing To Uncover Themes In Clinical Notes Of Patients Admitted For Heart Failure, Ankita Agarwal, Krishnaprasad Thirunarayan, William Romine, Amanuel Alambo, Mia Cajita, Tanvi Banerjee
Computer Science and Engineering Faculty Publications
Heart failure occurs when the heart is not able to pump blood and oxygen to support other organs in the body as it should. Treatments include medications and sometimes hospitalization. Patients with heart failure can have both cardiovascular as well as non-cardiovascular comorbidities. Clinical notes of patients with heart failure can be analyzed to gain insight into the topics discussed in these notes and the major comorbidities in these patients. In this regard, we apply machine learning techniques, such as topic modeling, to identify the major themes found in the clinical notes specific to the procedures performed on 1,200 patients …
Nomophobia Before And After The Covid-19 Pandemic-Can Social Media Be Used To Understand Mobile Phone Dependency, Vaishnavi Visweswaraiah, Tanvi Banerjee, William Romine, Sarah Fryman
Nomophobia Before And After The Covid-19 Pandemic-Can Social Media Be Used To Understand Mobile Phone Dependency, Vaishnavi Visweswaraiah, Tanvi Banerjee, William Romine, Sarah Fryman
Computer Science and Engineering Faculty Publications
No abstract provided.