The authors trained a machine learning model to detect kidney stones based on characteristics of urine. This method would allow for detection of kidney stones prior to the onset of noticeable symptoms by the patient.
Read More...A machine learning approach to detect renal calculi by studying the physical characteristics of urine
The authors trained a machine learning model to detect kidney stones based on characteristics of urine. This method would allow for detection of kidney stones prior to the onset of noticeable symptoms by the patient.
Read More...Analyzing resilience in a sample population as a novel qualifier for triage in psychological first aid
While serving as an immediate address for psychological safety and stability, psychological first aid (PFA) currently lacks the incorporation of triage. Without triage, patients cannot be prioritized in correspondence to condition severity that is often called for within emergency conditions. To disentangle the relevance of a potential triage system to PFA, the authors of this paper have developed a method to quantify resilience - a prominent predictor of the capability to recover from a disaster. With this resilience index, they have quantified resilience of differing age, race, and sex demographics to better inform the practice of PFA and potential demographic prioritization via a triage system.
Read More...Influence of socioeconomic status on academic performance in virtual classroom settings
In this study, the authors conduct a survey to evaluate the impact of household socioeconomic status on effectiveness of distance learning for students.
Read More...Applying centrality analysis on a protein interaction network to predict colorectal cancer driver genes
In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.
Read More...Post-Traumatic Stress Disorder (PTSD) biomarker identification using a deep learning model
In this study, a deep learning model is used to classify post-traumatic stress disorder patients through novel markers to assist in finding candidate biomarkers for the disorder.
Read More...EEG study of virtual learning demonstrates worsened learning outcomes and increased mirror neuron activation
In this article, Choi and Rossitto investigated the limitations of virtual learning by examining in-person dance learning compared to virtual dance learning while wearing EEG headsets. They found that in-person learners outperformed virtual learners and that virtual learners had higher mirror neuron activity as assessed by Mu rhythm power.
Read More...Environmental, social, and governance ratings and firm performance: Evidence from the Chinese stock market
Large corporations often are known for their financial power, but what social and environmental power and conscious do they have? The more responsible corporations are in relation to environmental, social, and governance criteria the better they do fiscally.
Read More...Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease
Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).
Read More...Comparing Consumer Personality and Brand Personality: Do Fashion Styles Speak of Who You Are?
This study investigated how fashion brand personalities are similar to people’s personalities and whether people may prefer a particular clothing brand based on their own personal traits. All together, Stevenson and Scott found that the Big Five Personality Factors are generally not related to participants’ preferred brand personalities. Generally, brands should consider different factors besides the Big Five Personality Factors for identifying potential customers.
Read More...Modulation of Planaria Regeneration by Resolvin D1 and the Omega-3 Fatty Acid Precursor 17-Hydroxy Docosahexaenoic Acid
Omega-3 fatty acid derived lipid mediators have been implicated in resolving inflammation, and wound healing. Authors measured the impact of supplementation with lipid mediator Resolvin D1 and its precursor 17-HDHA on planaria regeneration. Planaria not only synthesize RvD1 from 17-DHA, but both RvD1 and 17-DHA enhanced regeneration.
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