Results 161 to 170 of about 340,452 (356)
AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley +1 more source
Biology, ecology, and taxonomy of the parasitoids of the families of Austroniidae, Peradeniidae, Proctorenyxidae, Roproniidae, and Vanhorniidae (Hymenoptera: Proctotrupoidea) [PDF]
Carlos Henrique Marchiori +2 more
openalex +1 more source
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing +4 more
wiley +1 more source
Whales, fish and Alaskan bears: interest-relative taxonomy and kind pluralism in biology [PDF]
Henry Taylor
openalex +1 more source
This article offers a comprehensive review of topic modeling techniques, tracing their evolution from inception to recent developments. It explores methods such as latent Dirichlet allocation, latent semantic analysis, non‐negative matrix factorization, probabilistic latent semantic analysis, Top2Vec, and BERTopic, highlighting their strengths ...
Pratima Kumari +6 more
wiley +1 more source
There is a knowledge gap about the quantitative aspects of mycorrhizal fungi’s influence on ecological succession on tailings. Here, we demonstrate that inoculating mine tailings with 2% fungi yields significantly better results in terms of plant biomass
Aurora Neagoe +7 more
doaj +1 more source
The study presents a prototype novel workflow that utilizes artificial intelligence for the digitization of natural history collections, which would fit within a robotic‐integrated system. The work focuses on a collaborative‐robot (cobot) inspired workflow to digitize one of the largest collections housed at the Natural History Museum UK: pinned ...
Naifeng Zhang +4 more
wiley +1 more source
This review outlines how recurrent neural networks model multisensory integration by capturing temporal and probabilistic features of sensory input. Key developments, challenges, and future directions are summarized, providing insights into biologically inspired AI. Multisensory integration (MSI) is a core brain function underlying perception, learning,
Ehsan Bolhasani +2 more
wiley +1 more source

