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.
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Psychosocial impact of home-based learning among students during the COVID-19 Pandemic in Singapore
In this study, the authors surveyed a number of students in Singapore to determine how their experiences changed after the implementation of home-based learning during the COVID-19 pandemic.
Read More...Using text embedding models as text classifiers with medical data
This article describes the classification of medical text data using vector databases and text embedding. Various large language models were used to generate this medical data for the classification task.
Read More...pH-dependent drug interactions with acid reducing agents
Some cancer treatments lose efficacy when combined with treatments for excessive stomach acid, due to the changes in the stomach environment caused by the stomach acid treatments. Lin and Lin investigate information on oral cancer drugs to see what information is available on interactions of these drugs.
Read More...The correlation between bacteria and colorectal cancer
The authors looked at abundance of bacteria in stool samples from patients with colorectal cancer compared to controls. They found different bacteria that was more prevalent in patients with colorectal cancer as well as bacteria in control patients that may indicate a beneficial gut microbiome.
Read More...Epileptic seizure detection using machine learning on electroencephalogram data
The authors use machine learning and electroencephalogram data to propose a method for improving epilepsy diagnosis.
Read More...Adults’ attitudes toward non-alcoholic beer purchases and consumption by children and adolescents
Consumption of non-alcoholic beverages, like non-alcoholic beer, is growing in popularity in the United States. These beverages raise important societal questions, such as whether minors should be allowed to purchase or consume non-alcoholic beer. An and An investigate this issue by surveying adults to see if they support minors purchasing and consuming non-alcoholic beer.
Read More...Diagnosing hypertrophic cardiomyopathy using machine learning models on CMRs and EKGs of the heart
Here seeking to develop a method to diagnose, hypertrophic cardiomyopathy which can cause sudden cardiac death, the authors investigated the use of a convolutional neural network (CNN) and long short-term memory (LSTM) models to classify cardiac magnetic resonance and heart electrocardiogram scans. They found that the CNN model had a higher accuracy and precision and better other qualities, suggesting that machine learning models could be valuable tools to assist physicians in the diagnosis of hypertrophic cardiomyopathy.
Read More...Relating socioeconomic position (SEP) and vaccination with Covid-19 rates in select populations
This article describes the relationship between socioeconomic factors and the extent of how the COVID-19 Pandemic affected communities. Factors such as infection rate, vaccination rate, and economic status were all evaluated within the context of this article.
Read More...Differences in postoperative satisfaction between orthopedic and cosmetic patients
In this study, the authors investigate differences in psychological outcomes from patients who undergo different surgical procedures.
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