Improving Mental Health Outcomes through Machine Learning Feedback of Social Media Behavior

With mental health issues on the rise, the need for early diagnosis is especially pivotal to reduce the risk of suicide and disease. Both social media usage and social media content can act as indicators of a user’s mental health status. We posit that through using machine learning feedback, we can assist users in early self-diagnoses and monitor how that feedback affects their social media behavior and their mental health. By providing continuous feedback about users’ mental health, we can encourage users to change their social media habits and seek help from a mental health professional

Effect of Body Mass Index on Bleeding Frequency and Activated Partial Thromboplastin Time in Weight-Based Dosing of Unfractionated Heparin: A Retrospective Cohort Study

OBJECTIVE: To assess bleeding and activated partial thromboplastin time (APTT) in relation to body mass index (BMI) in patients prescribed weight-based dosing of intravenous unfractionated heparin (UFH) for cardiac indications without a maximum (dose-capped) initial bolus or capped initial infusion rate