Results 91 to 100 of about 18,832 (283)

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Detecting health misinformation: A comparative analysis of machine learning and graph convolutional networks in classification tasks

MethodsX
In the digital age, the proliferation of health-related information online has heightened the risk of misinformation, posing substantial threats to public well-being.
Bharti Khemani, Shruti Patil, Ketan Kotecha, Deepali Vora   +3 more
doaj   +1 more source

Rapoudok/GCN-herbal-medicine: 0.0.1

<p>Predicting new herbal prescriptions using GCNs</p ...
Tae-Hyoung Kim
core   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Epidermal growth factor receptor gene copy number in 101 advanced colorectal cancer patients treated with chemotherapy plus cetuximab

Journal of Translational Medicine, 2010
Background Responsiveness to Cetuximab alone can be mediated by an increase of Epidermal Growth factor Receptor (EGFR) Gene Copy Number (GCN). Aim of this study was to assess the role of EGFR-GCN in advanced colorectal cancer (CRC) patients receiving ...
Zeuli Massimo, Diodoro Maria, Conti Salvatore, Melucci Elisa, Sperduti Isabella, Merola Roberta, Torsello Angela, Cianciulli Anna, Mottolese Marcella, Campanella Carla, Paoletti Giancarlo, Cognetti Francesco, Garufi Carlo   +12 more
doaj   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Efficient generation of 1O2 by activating peroxymonosulfate on graphitic carbon nanoribbons for water remediation

npj Clean Water
Few-layer graphitic carbon nanoribbons (GCN) with rich defective sites were prepared by pyrolysis at 800 oC in N2 of in situ-chelated Fe-polyaniline complexes synthesized via one-pot homogeneous Fenton-like oxidative polymerization of an acidic aniline ...
Weijiang Tang, Zhengjie Wang, Sheng Guo, Rong Chen, Fengxi Chen   +4 more
doaj   +1 more source

EGFR gene copy number as a prognostic marker in colorectal cancer patients treated with cetuximab or panitumumab: a systematic review and meta analysis.

PLoS ONE, 2013
BackgroundThe epidermal growth factor receptor (EGFR) gene copy number (GCN) has been previously demonstrated to correlate with the clinical outcome of colorectal cancer (CRC) treated with anti-EGFR monoclonal antibodies (mAbs), although it remains ...
Zheng Jiang, Chunxiang Li, Fuyuan Li, Xishan Wang   +3 more
doaj   +1 more source