Results 191 to 200 of about 534,302 (284)
AI Ethics Is Not a Panacea. [PDF]
McLennan S, Lee MM, Fiske A, Celi LA.
europepmc +1 more source
Research and Practice of AI Ethics: A Case Study Approach Juxtaposing Academic Discourse with Organisational Reality. [PDF]
Ryan M +5 more
europepmc +1 more source
Real‐Time In Vivo Cellular‐Level Imaging During Puncture
We present an artificial‐intelligence‐empowered integrative‐light‐field microendoscopy (AIM) needle that delivers real‐time in vivo, diffraction‐limited cellular‐level imaging during puncture and visualizes layered microstructures along the needle path. As a microscopic complement to CT/ultrasound, it improves sampling localization and adds preliminary
Huifang Gao +13 more
wiley +1 more source
Neuroethics and AI ethics: a proposal for collaboration. [PDF]
Salles A, Farisco M.
europepmc +1 more source
General schematic of the approach. Abstract Conventional Silver/Silver Chloride (Ag/AgCl) electrodes remain the clinical standard for electrophysiological monitoring but are hindered by poor skin conformity, mechanical rigidity, and signal degradation, particularly under motion or sweat.
Nazmi Alsaafeen +11 more
wiley +1 more source
Reconstructing AI Ethics Principles: Rawlsian Ethics of Artificial Intelligence. [PDF]
Westerstrand S.
europepmc +1 more source
Five things every clinician should know about AI ethics in intensive care. [PDF]
Shaw JA, Sethi N, Block BL.
europepmc +1 more source
This study highlights the significance of non‐canonical splicing variants in male infertility, a factor often overlooked during the analysis of high‐throughput sequencing data. Incorporating the non‐canonical splicing variants prioritization in the genetic analysis pipeline will increase the genetic diagnosis of patients with male infertility ...
Kuokuo Li +22 more
wiley +1 more source
Navigating AI ethics: ANN and ANFIS for transparent and accountable project evaluation amidst contesting AI practices and technologies. [PDF]
Wankhade S +3 more
europepmc +1 more source
AI‐Driven Acceleration of Fluorescence Probe Discovery
We present PROBY, an AI model trained on large‐scale datasets to predict key photophysical properties and accelerate the discovery of target‐specific fluorescent probes. By screening a target‐annotated library, PROBY identifies candidate probes for diverse targets and could guide probe optimization, enabling a range of in vitro and in vivo imaging ...
Xuefeng Jiang +18 more
wiley +1 more source

