Pulmonary diseases like lung cancer and valley fever pose serious health challenges, making accurate and rapid diagnostics essential. This study developed a MATLAB-based software tool that uses computer vision techniques to differentiate between these diseases by analyzing features of lung nodules in CT scans, achieving higher precision than traditional methods.
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Unlocking robotic potential through modern organ segmentation
The authors looked at different models of semantic segmentation to determine which may be best used in the future for segmentation of CT scans to help diagnose certain conditions.
Read More...Convolutional neural network-based analysis of pediatric chest X-ray images for pneumonia detection
The authors test various machine learning models to improve the accuracy and efficiency of pneumonia diagnosis from X-ray images.
Read More...Calculating the dynamic viscosity of a fluid using image processing of a falling ball
The authors measure changes in the viscosity of glycerol with increasing temperature using the falling ball approach.
Read More...Identifying shark species using an AlexNet CNN model
The challenge of accurately identifying shark species is crucial for biodiversity monitoring but is often hindered by time-consuming and labor-intensive manual methods. To address this, SharkNet, a CNN model based on AlexNet, achieved 93% accuracy in classifying shark species using a limited dataset of 1,400 images across 14 species. SharkNet offers a more efficient and reliable solution for marine biologists and conservationists in species identification and environmental monitoring.
Read More...The effect of bioenhancers on ampicillin-sulbactam as a treatment against A. baumannii
This article explores the potential of piperine, a bioenhancer from black pepper, to improve antibiotic efficacy against antibiotic-resistant Acinetobacter baumannii. By combining piperine with ampicillin-sulbactam, the study demonstrated a significant reduction in bacterial growth for most strains tested, showcasing the promise of bioenhancers in combating resistant pathogens. This research highlights the possibility of reducing the required antibiotic dosage, potentially offering a new strategy in the fight against drug-resistant bacteria.
Read More...Trust in the use of artificial intelligence technology for treatment planning
As AI becomes more integrated into healthcare, public trust in AI-developed treatment plans remains a concern, especially for emotionally charged health decisions. In a study of 81 community college students, AI-created treatment plans received lower trust ratings compared to physician-developed plans, supporting the hypothesis. The study found no significant differences in AI trust levels across demographic factors, suggesting overall skepticism toward AI-driven healthcare.
Read More...Quantifying coliform bacteria in ground beef to evaluate food safety guidelines
The authors looked at the presence of coliform bacteria present in ground beef after cooking it various CDC standards. They found that no coliform bacteria was present when CDC guidelines for cooking ground beef were properly followed.
Read More...Low female employment rates in South Korea are linked to the gender-specific burden of childrearing
Female employment rates in South Korea are far below those of other countries that are members of the Organization for Economic Co-operation and Development. We assessed job satisfaction, job retention, and the underlying factors that impact these variables for both genders and various ages through a survey. Among 291 adult participants (161 women, 130 men) aged 20 to 59, working in various fields, 95% of responders were college graduates. These results suggest that even highly educated women feel more pressure from an innate sense of responsibility and societal perception to care for children than men.
Read More...Studying the effects of different anesthetics on quasi-periodic patterns in rat fMRI
The authors looked at the effects of commonly used anesthetics in rodents on brain activity (specifically quasi-periodic patterns). Understanding effects on brain activity is important for researchers to understand when choosing rodent models for disease.
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