Results 141 to 150 of about 90,813 (262)

Deciphering nodal burden in thyroid carcinoma: A dedicated survey of age, lymph node ratio, log odds of positive nodes, and preoperative prediction models

Journal of Intelligent Medicine, EarlyView.
Abstract Evidence regarding the prognosis of thyroid carcinoma is heterogeneous, ranging from age effects and nodal burden metrics, such as lymph node ratio (LNR) and log odds of positive nodes (LODDS), to preoperative imaging models comprising ultrasound, CEUS, and radiomics.
Mennatallah Sherif, Mohanad A. Deif, Eman K. Elsayed   +2 more
wiley   +1 more source

DeepSeek‐Lattice‐KG: A Compact Language Model With Knowledge Graph Augmentation for Lattice Structure Design

Materials Genome Engineering Advances, EarlyView.
DeepSeek‐Lattice‐KG integrates a domain‐adapted 14B LLM with a Neo4j lattice knowledge graph distilled from 50,000 papers. It analyzes queries, retrieves supporting subgraphs, and generates grounded answers; on a 2100‐question, six‐domain benchmark, it achieves 94.8% accuracy.
Zhiyang Shu, Chao Wang, Changsheng Feng, Feiyu Zhou, Xueyan Chen, Yan Chen, Yilun Liu   +6 more
wiley   +1 more source

Characteristics, properties and limitations of per‐ or polyfluoroalkyl substances (PFASs) and fluoropolymers

Polymer International, EarlyView.
An overview and categorization of man‐made per‐ or polyfluoroalkyl substances (PFASs) including low‐molar‐mass and high‐molar‐mass fluorochemicals, and their international regulations is presented. Though certain PFASs are toxic, bioaccumulative and cross the human cellular membranes, others, such as fluoropolymers, are safe, reliable and involved in ...
Bruno Améduri
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

Mining Biomedical Texts to Generate Semantic Annotations

, 2007
This report focuses on text mining in the biomedical domain for the generation of semantic annotations based on a formal model which is ontology. We start by exposing the generic methodology for the generation of annotations from texts. Then, we present a state of the art on different knowledge extraction techniques used on biomedical texts. We propose
Khelif, Khaled, Dieng-Kuntz, Rose, Barbry, Pascal   +2 more
openaire   +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

Introduction to BLAH5 special issue: recent progress on interoperability of biomedical text mining. [PDF]

Genomics Inform, 2019
Kim JD, Cohen KB, Collier N, Lu Z, Rinaldi F.   +4 more
europepmc   +1 more source

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

L‐VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts

Computer Graphics Forum, EarlyView.
L‐VISP is a human‐machine solution that uses visual analytics for LSTM modelling in clinical research. L‐VISP uses custom visual encodings to make multiple LSTM variants interpretable, supporting a full range of analysis, from understanding model operations and evaluating performance to interpreting results in a clinical context.
C. Floricel, Y. Wang, A. Wentzel, C. D. Fuller, G. E. Marai, M. E. Papka, G. Canahuate   +6 more
wiley   +1 more source

Inter‐disciplinary perspectives on sustainability in machinery manufacturing

International Journal of Management Reviews, EarlyView.
Abstract Perspectives on economic, social and environmental sustainability in machinery manufacturing are changing. These are predominantly driven by increased consumer, firm and public knowledge on the importance of sustainability and the role that machinery manufacturers can play to achieve sustainability outcomes.
Oluwaseun E. Olabode, Eleni Zantidou, Olaide F. Olabode, Afolakemi A. Jedidiah, Simon Fletcher, Andrew Longstaff   +5 more
wiley   +1 more source