日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

M-GNN: A Graph Neural Network Framework for Lung Cancer Detection Using Metabolomics and Heterogeneous Graph Modeling.

M-GNN:一种利用代谢组学和异构图建模进行肺癌检测的图神经网络框架

Vaida Maria, Wu Jiawen, Himdiat Eyad, Haince Jean-François, Bux Rashid A, Huang Guoyu, Tappia Paramjit S, Ramjiawan Bram, Ford W Rand

Multimodal graph neural networks in healthcare: a review of fusion strategies across biomedical domains

多模态图神经网络在医疗保健领域的应用:跨生物医学领域的融合策略综述

Vaida, Maria; Huang, Ziyuan

ADAM-1: An AI Reasoning and Bioinformatics Model for Alzheimer's Disease Detection and Microbiome-Clinical Data Integration

ADAM-1:用于阿尔茨海默病检测和微生物组-临床数据整合的人工智能推理和生物信息学模型

Huang, Ziyuan; Kaur Sekhon, Vishaldeep; Sadeghian, Roozbeh; Vaida, Maria L; Jo, Cynthia; McCormick, Beth A; Ward, Doyle V; Bucci, Vanni; Haran, John P

Translational impact of machine learning-driven predictive modeling with pathway-based plasma metabolomic biomarkers for lung cancer detection

基于通路血浆代谢组学生物标志物的机器学习驱动预测模型在肺癌检测中的转化应用

Himdiat, Eyad; Haince, Jean-François; Bux, Rashid A; Huang, Guoyu; Tappia, Paramjit S; Ramjiawan, Bram; Vaida, Maria

Identification of a Novel Biomarker Panel for Breast Cancer Screening

鉴定一种用于乳腺癌筛查的新型生物标志物组合

Vaida, Maria; Arumalla, Kamala K; Tatikonda, Pavan Kumar; Popuri, Bharadwaj; Bux, Rashid A; Tappia, Paramjit S; Huang, Guoyu; Haince, Jean-François; Ford, W Randolph

Metabolomics-Based Machine Learning Models Accurately Predict Breast Cancer Estrogen Receptor Status

基于代谢组学的机器学习模型能够准确预测乳腺癌雌激素受体状态

Arumalla, Kamala K; Haince, Jean-François; Bux, Rashid A; Huang, Guoyu; Tappia, Paramjit S; Ramjiawan, Bram; Ford, W Randolph; Vaida, Maria