We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.

In her 2001 paper “Predictors of Postpartum Depression: An Update,” researcher Cheryl Tatano Beck presents the most common risk factors associated with postpartum depression in women. Postpartum depression occurs when women experience symptoms such as tearfulness, extreme mood changes, and loss of appetite for a lengthened period after giving birth. At the University of Connecticut in Storrs, Connecticut, nursing professor Beck updated a previous study of hers by analyzing literature about postpartum depression published in the 1990s. Beck found four predictors of postpartum depression that she had not included in her previous study. “Predictors of Postpartum Depression: An Update” presents risk factors that healthcare professionals can use to predict whether pregnant women are more likely to develop postpartum depression.

In 2004, Shu-Shya Heh, Lindsey Coombes, and Helen Bartlett studied the association between Chinese postpartum (post-childbirth) practices and postpartum depression in Taiwanese women. The researchers surveyed Taiwanese women about the social support they received after giving birth and then evaluated the depression rates in the same women. Heh and her colleagues focused on the month following childbirth, which according to traditional Chinese medicine, is an important period that warrants a set of specialized practices to aid the woman's recovery. Collectively called zuoyuezi (doing the month), the postpartum practices require the help of someone else, typically the woman's mother or mother-in-law, to complete. Heh and her colleagues found that generally, Taiwanese women with more social support displayed fewer postpartum depressive symptoms, and concluded that the practice of doing the month helped prevent postpartum depression in Taiwanese women.

In 2011, Sarah McMahon and colleagues published “The Impact of Emotional and Physical Violence During Pregnancy on Maternal and Child Health at One Year Post-partum,” hereafter, “The Impact,” in the journal, Child and Youth Services Review. While existing studies had indicated negative chronic effects resulting from intimate partner violence, or IPV, such as miscarriage and premature labor, there was little research specifically analyzing the separate and joint effects of psychological and physical abuse on pregnant women and fetuses. The authors reported that both physical and emotional IPV had negative impacts on the woman and child at one-year after birth, including worse overall health and increased likelihood of depression. In “The Impact,” the researchers analyzed the effects of partner abuse during pregnancy, distinguishing between the effects of emotional abuse and physical abuse on health outcomes for a pregnant woman and her offspring.

The field of veterinary medicine can be rewarding, but also very demanding. Research has shown that many practicing veterinarians struggle with mental illness, and the profession has one of the highest suicide rates in the United States. Research has also shown that many veterinary students struggle with mental illness. It is important to further research the mental health of veterinary students and how that can correlate with one's mental health as a practicing veterinarian. The purpose of this project is to summarize findings of the literature concerning the mental health of veterinary students and to present a new resource, the Wisdom Vet app, that can potentially support the well-being of veterinary students.