The electronic health record (EHR), along with its mobile application, has demonstrated the ability to improve the efficiency and accuracy of health care delivery. This study included data from 874 health care providers over a 12-month period regarding their usage of mobile phone (EPIC® Haiku) and tablet (EPIC® Canto) mEHR. Ambulatory and inpatient care providers had the greatest usage levels over the 12-month period. Awareness of workflow allows for optimization of mEHR design and implementation, which should increase mEHR adoption and usage, leading to better health outcomes for patients.
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Evaluating the effectiveness of machine learning models for detecting AI-generated art
The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.
Read More...Building a video classifier to improve the accuracy of depth-aware frame interpolation
In this study, the authors share their work on improving the frame rate of videos to reduce data sent to users with both 2D and 3D footage. This work helps improve the experience for both types of footage!
Read More...The Effect of Radiant Energy on Radish Seed Germination
Simon and colleagues test how exposure to microwaves affect radish seed germination, either microwaving seeds for ninety seconds or four minutes prior to planting. Surprisingly, the authors found that seeds microwaved for four minutes exhibited 150% increased germination as compared to controls. The authors hypothesize that breakdown of the radish seed coat when exposed to heat may allow seedlings to sprout more efficiently.
Read More...The gender gap in STEM at top U.S. Universities: change over time and relationship with ranking
Authors address the gender disparity in STEM fields, examining changes in gender diversity across male-dominated undergraduate programs over 19 years at 24 top universities. Analyzing data from NCES IPEDS, it identifies STEM as persistently male-dominated but notes increasing gender diversity in many disciplines, particularly in recent years. Results indicate that higher-ranked universities in disciplines like computer science and mechanical engineering show a weak correlation with improved gender diversity, suggesting effective initiatives can mitigate the gender gap in STEM, despite ongoing challenges.
Read More...Long Range Radio Communication for Urban Sensor Networks
This study investigates the feasibility of using long-range radio communication in a busy city environment in order to begin better understanding how the Internet of Things might be implemented into smart cities.
Read More...Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes
People with Type One diabetes often rely on Continuous Blood Glucose Monitors (CGMs) to track their blood glucose and manage their condition. Researchers are now working to help people with Type One diabetes more easily monitor their health by developing models that will future blood glucose levels based on CGM readings. Jalla and Ghanta tackle this issue by exploring the use of AI models to forecast blood glucose levels with CGM data.
Read More...Changing electronic use behavior in adolescents while studying: An interventional psychology experiment
Here, the authors investigated the effects of an interventional psychology on the study habits of high school students specifically related to the use of electronic distractions such as social media or texting, listening to music, or watching TV. They reported varying degrees of success between the control and intervention groups, suggesting that the methods of habit-breaking for students merits further study.
Read More...Failure of colony growth in probiotic Lactobacillus casei Shirota as result of preservative sorbic acid
This study tested the proficiency of different concentrations of the antimicrobial sorbic acid to inhibit the probiotic Lactobacillus casei Shirota. It was hypothesized that sorbic acid’s use as a bacterial deterrent would also target this bacterial strain of Lactobacillus. The results supported the hypothesis, with the colony count of L. casei Shirota having significant decreases at all concentrations of sorbic acid. These results additionally suggest that even under the FDA sorbic acid restrictions of 0.03% concentration, damaging effects could be seen in L. casei Shirota.
Read More...A natural language processing approach to skill identification in the job market
The authors looked at using machine learning to identify skills needed to apply for certain jobs, specifically looking at different techniques to parse apart the text. They found that Bidirectional Encoder Representation of Transforms (BERT) performed best.
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