![Prediction of diabetes using supervised classification](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBb1VRIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--ddab2529bca9f7b67cee56366c32a1a4906d0e48/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJY0c1bkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--33b2b080106a274a4ca568f8742d366d42f20c14/feature.png)
The authors develop and test a machine learning algorithm for predicting diabetes diagnoses.
Read More...Prediction of diabetes using supervised classification
The authors develop and test a machine learning algorithm for predicting diabetes diagnoses.
Read More...Battling cultural bias within hate speech detection: An experimental correlation analysis
The authors develop a new method for training machine learning algorithms to differentiate between hate speech and cultural speech in online platforms.
Read More...Computational development of aryl sulfone compounds as potential NNRTIs
Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors that bind to the HIV reverse transcriptase and prevent replication. Indolyl aryl sulfones (IAS) and IAS derivatives have been found to be highly effective against mutant strains of HIV-1 reverse transcriptase. Here, we analyzed molecules designed using aryl sulfone scaffolds paired to cyclic compounds as potential NNRTIs through the computational design and docking of 100 novel NNRTI candidates. Moreover, we explored the specific combinations of functional groups and aryl sulfones that resulted in the NNRTI candidates with the strongest binding affinity while testing all compounds for carcinogenicity. We hypothesized that the combination of an IAS scaffold and pyrimidine would produce the compounds with the best binding affinity. Our hypothesis was correct as the series of molecules with an IAS scaffold and pyrimidine exhibited the best average binding affinity. Additionally, this study found 32 molecules designed in this procedure with higher or equal binding affinities to the previously successful IAS derivative 5-bromo-3-[(3,5-dimethylphenyl)sulfonyl]indole-2-carboxyamide when docked to HIV-1 reverse transcriptase.
Read More...Machine learning for the diagnosis of malaria: a pilot study of transfer learning techniques
The diagnosis of malaria remains one of the major hurdles to eradicating the disease, especially among poorer populations. Here, the authors use machine learning to improve the accuracy of deep learning algorithms that automate the diagnosis of malaria using images of blood smears from patients, which could make diagnosis easier and faster for many.
Read More...A cost-effective IoT-based intelligent indoor air quality monitoring
Poor air quality is associated with negative effects on human health but can be difficult to measure in an accurate and cost-effective manner. The authors design and test a monitor for measuring indoor air quality using low-cost components.
Read More...Estimating the elastic modulus and bending stiffness of steel ruler with crack using three-point bending test
In this study the authors look at elastic modulus and stiffness of steel rules with vary lengths of cracks. They found that cracks decreased the overall elastic modulus and bending stiffness of the ruler. This work has applications to structural engineering and the design of items such as airplanes and bridges.
Read More...Differences in Reliability and Predictability of Harvested Energy from Battery-less Intermittently Powered Systems
Solar and radio frequency harvesters serve as a viable alternative energy source to batteries in many cases where the battery cannot be easily replaced. Using specifically designed circuit models, the authors quantify the reliability of different harvested energy sources to identify the most practical and efficient forms of renewable energy.
Read More...Pruning replay buffer for efficient training of deep reinforcement learning
Reinforcement learning (RL) is a form of machine learning that can be harnessed to develop artificial intelligence by exposing the intelligence to multiple generations of data. The study demonstrates how reply buffer reward mechanics can inform the creation of new pruning methods to improve RL efficiency.
Read More...Demographic indicators of voter shift between 2016 and 2020 presidential elections
In this study, the authors investigate the demographic indicators for voter shift between the 2016 and 2020 presidential elections based on demographic data put through a K-nearest neighbors classification algorithm and Principal Component Analysis.
Read More...Estimation of Reproduction Number of Influenza in Greece using SIR Model
In this study, we developed an algorithm to estimate the contact rate and the average infectious period of influenza using a Susceptible, Infected, and Recovered (SIR) epidemic model. The parameters in this model were estimated using data on infected Greek individuals collected from the National Public Health Organization. Our model labeled influenza as an epidemic with a basic reproduction value greater than one.
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