The authors develop a machine learning method to reduce misclassification of objects in safety-critical applications such as medical diagnosis.
Read More...Mitigating open-set misclassification in a colorectal cancer detecting neural network
The authors develop a machine learning method to reduce misclassification of objects in safety-critical applications such as medical diagnosis.
Read More...Lung cancer AI-based diagnosis through multi-modal integration of clinical and imaging data
Lung cancer is highly fatal, largely due to late diagnoses, but early detection can greatly improve survival. This study developed three models to enhance early diagnosis: an MLP for clinical data, a CNN for imaging data, and a hybrid model combining both.
Read More...Levering machine learning to distinguish between optimal and suboptimal basketball shooting forms
The authors looked at different ways to build computational resources that would analyze shooting form for basketball players.
Read More...The optimization of high-protein duckweed cultivation in eutrophicated water with mutualistic bacteria
he rapid growth of the human population is driving food crises in Thailand and Southeast Asia, while contributing to global food insecurity and a larger carbon footprint. One potential solution is cultivating duckweed (Wolffia globosa) for consumption, as it grows quickly and can provide an alternative protein source. This research explored two methods to optimize duckweed cultivation: using phosphorus- and nitrogen-rich growing media and plant growth-promoting bacteria (PGPB).
Read More...Recombinant preparation and characterization of ADH1C and ALDH2 in alcohol metabolism
The authors test the activity of two purified human alcohol detoxification enzymes, alcohol dehydrogenase and aldehyde dehydrogenase.
Read More...Genetic Bioaugmentation of Oryza sativa to Facilitate Self-Detoxification of Arsenic In-Situ
Arsenic contamination in rice, caused by the use of arsenic-laden groundwater for irrigation, is a growing global concern, affecting over 150 million people. To address this, researchers hypothesized that genetically modifying rice plants with arsenic-resistant genes could reduce arsenic uptake and allow the plants to detoxify arsenic, making them safer to consume.
Read More...Evaluating the antimicrobial activity of maitake mushroom extract against Staphylococcus epidermidis
Here, seeking to explore new antimicrobial therapies, the authors investigated the antimicrobial activity of Maitake mushroom extract against Staphylococcus epidermidis, a common cause of antibiotic resistant hospital-acquired infections. They found that Maitake extract showed potent antimicrobial activity, with higher concentrations showing inhibition comparable to tetracycline.
Read More...Synthesis of sodium alginate composite bioplastic films
The authors looked at the development of biodegradable bioplastic and its features compared to PET packaging films. They were able to develop a biodegradable plastic with sodium alginate that dissolved in water and degrade in microbial conditions while also being transparent and flexible similar to current plastic films.
Read More...Investigating momentum transfer with gall-forming wasps
The authors use the unique movements of the jumping gall wasp to study momentum transfer with potential applications in robotics and extraterrestrial research.
Read More...The effect of youth marijuana use on high-risk drug use: Examining gateway and substitution hypothesis
The authors looked at whether youth use of marijuana related to later high-risk drug use. Using survey data from 2010-2019 they found that youth marijuana use did correlate to an increased risk of high-risk drug use.
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