The authors looked at the ability to detect heart disease before the onset of severe clinical symptoms.
Read More...Study of neural network parameters in detecting heart disease
The authors looked at the ability to detect heart disease before the onset of severe clinical symptoms.
Read More...Deep dive into predicting insurance premiums using machine learning
The authors looked at different factors, such as age, pre-existing conditions, and geographic region, and their ability to predict what an individual's health insurance premium would be.
Read More...Novel biaryl imines and amines as potential competitive inhibitors of dihydropteroate synthase
In this study, the authors design a series of new biaryl small molecules to target and block the binding pocket of the enzyme dihydropteroate synthase, which is important for prokaryotic biosynthesis of folic acid and could serve as better antimicrobial compounds.
Read More...Slowing ice melting from thermal radiation using sustainable, eco-friendly eggshells
The authors looked at the ability of eggshells to slow ice melting. They found that eggshells were able to increase ice melting time when crushed showing that they were an effective thermal barrier.
Read More...Stress and depression among individuals with low socioeconomic status during economic inflation
The authors use the Census Household Pulse Survey issued by the US Census Bureau to examine the prevalence of stress and depression among people across socioeconomic statuses.
Read More...Substance Abuse Transmission-Impact of Parental Exposure to Nicotine/Alcohol on Regenerated Planaria Offspring
The global mental health crisis has led to increased substance abuse among youth. Prescription drug abuse causes approximately 115 American deaths daily. Understanding intergenerational transmission of substance abuse is complex due to lengthy human studies and socioeconomic variables. Recent FDA guidelines mandate abuse liability testing for neuro-active drugs but overlook intergenerational transfer. Brown planaria, due to their nervous system development similarities with mammals, offer a novel model.
Read More...Quantitative analysis and development of alopecia areata classification frameworks
This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.
Read More...High school students’ attitudes towards diverse cultures and ethnicities
The authors looked at how a student's own background influence their attitude towards integration of diverse cultures and ethnicities. While overall students viewed other groups positively, the authors found that groups still indicated they felt judged by their peers.
Read More...Identifying factors, such as low sleep quality, that predict suicidal thoughts using machine learning
Sadly, around 800,000 people die by suicide worldwide each year. Dong and Pearce analyze health survey data to identify associations between suicidal ideation and relevant variables, such as sleep quality, hopelessness, and anxious behavior.
Read More...Who controls U.S. politics? An analysis of major political endorsements in U.S. midterm elections
The authors analyze political endorsement patterns and impacts from the 2018 and 2020 midterm elections and find that such endorsements may be predictable based on the ideological and demographic factors of the endorser.
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