Technology convergence prediction based on temporal heterogeneous graph neural networks DOI
Hui Li, Haozhao Liang, Yaohua Hu

et al.

Information Processing & Management, Journal Year: 2024, Volume and Issue: 62(3), P. 104034 - 104034

Published: Dec. 21, 2024

Language: Английский

A Scoping Review of Artificial Intelligence Applications in Clinical Trial Risk Assessment DOI Creative Commons
Douglas Teodoro, Nona Naderi, Anthony Yazdani

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 22, 2025

Abstract Artificial intelligence (AI) is increasingly applied to clinical trial risk assessment, aiming improve safety and efficiency. This scoping review analyzes 142 studies published between 2013 2024, focusing on (n=55), efficacy (n=46), operational (n=45) prediction. AI techniques, including traditional machine learning, deep learning (e.g., graph neural networks, transformers), causal are used for tasks like adverse drug event prediction, treatment effect estimation, phase transition These methods utilize diverse data sources, from molecular structures protocols patient scientific publications. Recently, large language models (LLMs) have seen a surge in applications, representing over 20% of 2023. While some achieve high performance (AUROC up 96%), challenges remain, selection bias, limited prospective studies, quality issues. Despite these limitations, AI-based assessment holds substantial promise transforming trials, particularly through improved risk-based monitoring frameworks.

Language: Английский

Citations

0
Identifying and evaluating R&D partners via patent-based multilayer networks from the perspective of knowledge complementarity: A case study of unmanned ship technology DOI
Jinfeng Wang,

Ningtao Wang,

Weiyu Zhao

et al.

Computers & Industrial Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 111085 - 111085

Published: April 1, 2025

Language: Английский

Citations

0
Generating firm-centric technology opportunities from patent recommendation: a dual link prediction perspective DOI

Zhenfeng Liu,

Xinyu Wang, Feng Jian

et al.

Technology Analysis and Strategic Management, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 18

Published: April 20, 2025

Language: Английский

Citations

0
Increasing the efficiency of gene editing with CRISPR-Cas9 via concurrent expression of the Beta protein DOI
Weiyu Zhao, Yanan Guo

International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 270, P. 132431 - 132431

Published: May 15, 2024

Language: Английский

Citations

3
Exploring the Technological Leaders Using Tire Industry Patents: A Topic Modeling Approach DOI
Mohsen Ghaffari, Alireza Aliahmadi, Abolfazl Khalkhali

et al.

Technology in Society, Journal Year: 2024, Volume and Issue: 78, P. 102664 - 102664

Published: Sept. 1, 2024

Language: Английский

Citations

2
Dynamic elicitation and forecasting innovation requirement of smart product-service system via user-manufacturer value co-creation perspective using multi-source data DOI
Jinfeng Wang,

Keyuan Sun,

Peng Liu

et al.

Computers & Industrial Engineering, Journal Year: 2024, Volume and Issue: 197, P. 110511 - 110511

Published: Aug. 22, 2024

Language: Английский

Citations

1
Deep Learning Approaches for Understanding Adverse Drug Reaction: Short Literature Review DOI

Chaimaa Zyani,

El Habib Nfaoui

Lecture notes in networks and systems, Journal Year: 2024, Volume and Issue: unknown, P. 536 - 544

Published: Jan. 1, 2024

Language: Английский

Citations

0
Technology convergence prediction based on temporal heterogeneous graph neural networks DOI
Hui Li, Haozhao Liang, Yaohua Hu

et al.

Information Processing & Management, Journal Year: 2024, Volume and Issue: 62(3), P. 104034 - 104034

Published: Dec. 21, 2024

Language: Английский

Citations

0