Stanford researchers argue that healthcare AI translation needs to focus on more than just linguistic accuracy for true effectiveness.

Abstract: This paper searches for the optimal neural architecture by minimizing a proxy of validation loss. Existing neural architecture search (NAS) methods used to discover the optimal neural ...

A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.

The integration of artificial intelligence (AI) in voice biomarker analysis presents a transformative opportunity for objective and non-invasive diagnostics in healthcare. However, clinical adoption ...

The Workshop is planned to highlight, review, and discuss issues related to the implementation of XRF methodologies, including addressing recommendations for compliance to technical requirements of ...

Validation of an analytical method provides evidence that when correctly applied, it produces results that are fit for purpose, thereby demonstrating the effectiveness of the method with an acceptable ...

The quality of traditional Chinese medicine (TCM) guarantees clinical efficacy. At present, although chemical quality evaluation methods can reflect the quality of TCMs to a certain extent, there are ...

Abstract: The complexity and uncertainty of deep neural networks (DNN) necessitate comprehensive behavior testing for model quality assurance. Current studies generating samples via coverage criteria ...

This talk will focus on doing method validation work in an environment where data is gathered from laboratory information systems and chromatography data systems. We’ll see how these systems can be ...