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Trust in the use of artificial intelligence technology for treatment planning

Srivastava et al. | Sep 18, 2024

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.

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Phytoplankton Plastid Proteomics: Cracking Open Diatoms to Understand Plastid Biochemistry Under Iron Limitation

Nunn et al. | Feb 10, 2017

Phytoplankton Plastid Proteomics: Cracking Open Diatoms to Understand Plastid Biochemistry Under Iron Limitation

In many areas of the world’s oceans, diatoms such as Thalassiosira pseudonana are limited in growth by the availability of iron (Fe), which is an essential nutrient for diatoms. The authors of this study examined if Fe-limitation makes a significant difference in the proteins expressed within the chloroplast, the power source for diatoms, utilizing a new plastid isolation technique specific to diatoms and completing 14 mass spectrometry experiments.

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Open Source RNN designed for text generation is capable of composing music similar to Baroque composers

Goel et al. | May 05, 2021

Open Source RNN designed for text generation is capable of composing music similar to Baroque composers

Recurrent neural networks (RNNs) are useful for text generation since they can generate outputs in the context of previous ones. Baroque music and language are similar, as every word or note exists in context with others, and they both follow strict rules. The authors hypothesized that if we represent music in a text format, an RNN designed to generate language could train on it and create music structurally similar to Bach’s. They found that the music generated by our RNN shared a similar structure with Bach’s music in the input dataset, while Bachbot’s outputs are significantly different from this experiment’s outputs and thus are less similar to Bach’s repertoire compared to our algorithm.

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