Results 211 to 220 of about 200,089 (297)
Helena Webb +8 more
openaire +1 more source
The integration of Artificial Intelligence (AI) in healthcare and other safety-critical domains requires rigorous verification of the correct behaviour of AI systems, including their reliability, transparency and fairness, in order to meet stringent ...
Rejzek, Martin +2 more
core
A synergistic approach using phenethylammonium iodide (PEAI) and antimony iodide (SbI3) enhances the operational stabilities of perovskite solar cells by providing p‐type doping effect, suitable band energy alignment, reduced defect density, and minimized surface ion vacancies in the perovskite films.
Abraham Adenle +17 more
wiley +1 more source
The imperative of diversity and equity for the adoption of responsible AI in healthcare. [PDF]
Hilling DE +5 more
europepmc +1 more source
When a master transcription factor (TF) is lost, bacteria can rapidly rewire gene regulatory networks by co‐opting related regulators. Using experimental evolution in Pseudomonas fluorescens, we show that TF promiscuity (low‐level, non‐cognate binding) provides the raw material for rewiring. Successful co‐option follows a predictable hierarchy governed
Tiffany B. Taylor, Alan M. Rice
wiley +1 more source
Collaborative framework on responsible AI in LLM-driven CDSS for precision oncology leveraging real-world patient data. [PDF]
Mathes S +16 more
europepmc +1 more source
We propose the Full‐Body AI Agent, a multi‐scale collaborative framework with 7 biological‐layer agents. It unifies multi‐omics/clinical data via standardized protocols, enabling phenotype‐guided closed‐loop reasoning, quantitative evaluation, and LLM safeguards, with promising applications in tumor metastasis modeling and precision drug development ...
Aoqi Wang +11 more
wiley +1 more source
Collaborative and Cooperative Hospital "In-House" Medical Device Development and Implementation in the AI Age: The European Responsible AI Development (EURAID) Framework Compatible With European Values. [PDF]
Schönfelder A +26 more
europepmc +1 more source
Machine‐Learning Microfluidic Minute‐Scale Microorganism Metrics Monitoring(M6)
ABSTRACT On‐site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol‐transmitted pathogens. Here, we report a rapid detection platform that integrates a Puri‐focusing microfluidic chip, electrochemical impedance spectroscopy (EIS), and ...
Ning Yang +14 more
wiley +1 more source
Responsible AI in student management: preventing misdecision in career choice of university students under inaccurate guidance. [PDF]
Yin S +4 more
europepmc +1 more source

