Results 131 to 140 of about 43,712,030 (248)

A Scalable Large Language Model‐Aided Approach for Mining Plant‐Compound Pairs From Scientific Literature

PLANTS, PEOPLE, PLANET, EarlyView.
Understanding plant chemicals is vital for medicine and agriculture, but global data remain fragmented and biased. We developed an AI‐powered tool to automatically extract plant‐compound information from scientific literature at scale and low cost. Our analysis revealed significant knowledge gaps, particularly in the Southern Hemisphere. By efficiently
Adam Richard‐Bollans, Francesco Civita
wiley   +1 more source

Automatic insect identification, counting, and monitoring techniques: a review

Pest Management Science, EarlyView.
Automated insect monitoring increasingly integrates optical, acoustic, infrared, radar, electrostatic, and biosensing technologies with artificial intelligence. No single approach is universally optimal; reliable deployment depends on task‐specific validation, representative datasets, robustness under field conditions, energy autonomy, connectivity ...
Mariano González García, Juan Carlos Noguera Polania, Rosana González Combarros, José Ignacio López Sánchez   +3 more
wiley   +1 more source

Information Retrieval Architecture for Text Mining of Biomedical Literature

, 2008
Text Mining for Biomedical domain is an active area of research that is seeing a plethora of new tools and techniques to accomplish its purpose. All these systems mostly try to integrate the Medline database, other databases that describe about the ...
Cs Spring
core  

Artificial Intelligence for Precision Phytomedicine: A Critical Review and the Patient–Product–Mechanism–Response (PPMR) Framework

Phytotherapy Research, EarlyView.
PPMR framework for precision phytomedicine: AI and computational pharmacology for joint patient–product characterization, with staged validation along the evidence continuum (T1–T5). Created in BioRender. Elsagheir, A. M. K. (2026) https://BioRender.com/i9y6l7t.
Mohamed Fared Shawky Mohamed, Ahmed Mohsen Kamal El‐sagheir, Jen Chin Lin, Ming‐Kuem Lin, Yung‐Luen Yu, Jung Chao   +5 more
wiley   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Carbon dots in photocatalytic water splitting and related proton/electron‐coupled reactions: Multiscale regulation of charge dynamics and interfacial processes

Responsive Materials, EarlyView.
This review summarizes CD‐based photocatalytic water splitting as a multiscale charge‐utilization process, linking photoexcitation, charge separation, interfacial transfer, charge storage, and catalytic consumption. It highlights how CD structures and interfaces regulate charge pathways and reaction microenvironments, and how advanced characterization,
Fan Liao, Yang Liu, Zhenhui Kang
wiley   +1 more source

Recent Advances and Challenges in Single‐Atom Catalysts for Thermocatalytic CO2 Hydrogenation

Small, EarlyView.
Single‐atom catalysts (SACs) offer atomically precise platforms to control thermocatalytic CO2 hydrogenation pathways. This Review highlights how coordination environment, charge transfer, and metal–support interactions govern selectivity from CO to CH4, CH3OH, and C2+ products.
Ping Chen, Xin Zhang, Honghong Shi
wiley   +1 more source

Review on enhancing clinical decision support system using machine learning

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood, Usman Naseem, Junaid Rashid, Jungeun Kim, Imran Razzak   +4 more
wiley   +1 more source

POSBIOTM/W: A Development Workbench For Machine Learning Oriented Biomedical Text Mining System ∗

, 2008
The POSBIOTM/W 1 is a workbench for machine-learning oriented biomedical text mining system. The POSTBIOTM/W is intended to assist biologist in mining useful information efficiently from biomedical text resources.
Yu Song, Kyungduk Kim, Gary Geunbae Lee
core  

Text mining for case report articles on “peritoneal dialysis” from PubMed database

Therapeutic Apheresis and Dialysis, Volume 29, Issue 3, Page 459-470, June 2025.
Abstract Introduction The number of published medical articles on peritoneal dialysis (PD) has been increasing, and efficiently selecting information from numerous articles can be difficult. In this study, we examined whether artificial intelligence (AI) text mining can be a good support for efficiently collecting PD information.
Kazuhiko Fukushima, Kenji Tsuji, Hiroyuki Nakanoh, Naruhiko Uchida, Soichiro Haraguchi, Shinji Kitamura, Jun Wada   +6 more
wiley   +1 more source