A5055495624- Computational Drug Discovery Methods
- Radiomics and Machine Learning in Medical Imaging
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Cancer Immunotherapy and Biomarkers
- Artificial Intelligence in Healthcare
- Protein Structure and Dynamics
- Colorectal Cancer Treatments and Studies
- Lung Cancer Treatments and Mutations
- Ferroptosis and cancer prognosis
- Machine Learning in Materials Science
- Diabetes Management and Research
- Diabetes, Cardiovascular Risks, and Lipoproteins
Shanghai Artificial Intelligence Laboratory
2022-2023
Beijing Academy of Artificial Intelligence
2022-2023
Pathway-based analysis of transcriptomic data has shown greater stability and better performance than traditional gene-based analysis. Until now, some pathway-based deep learning models have been developed for bioinformatic analysis, but these not fully considered the topological features pathways, which limits final prediction result.To address this issue, we propose a novel model, called PathGNN, constructs Graph Neural Networks (GNNs) model that can capture pathways. As case, PathGNN was...
The availability of high-throughput sequencing data creates opportunities to comprehensively understand human diseases as well challenges train machine learning models using such high dimensions data. Here, we propose a denoised multi-omics integration framework, which contains distribution-based feature denoising algorithm, Feature Selection with Distribution (FSD), for dimension reduction and Attention Multi-Omics Integration (AttentionMOI) predict cancer prognosis identify subtypes. We...
Abstract Motivation Proteins play crucial roles in biological processes, with their functions being closely tied to thermodynamic stability. However, measuring stability changes upon point mutations of amino acid residues using physical methods can be time-consuming. In recent years, several computational for protein prediction (PTSP) based on deep learning have emerged. Nevertheless, these approaches either overlook the natural topology structures or neglect inherent noisy samples resulting...
Clinical guidelines for the management of individuals with type 2 diabetes mellitus endorse systematic assessment atherosclerotic cardiovascular disease risk early interventions. In this study, we aimed to develop machine learning models predict 3-year in Chinese patients.Clinical records 4,722 admitted 94 hospitals were used. The features included demographic information, histories, laboratory tests and physical examinations. Logistic regression, support vector machine, gradient boosting...
Immunotherapy has improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), but only a small subset achieved clinical benefit.The purpose our study was to integrate multidimensional data using machine learning method predict therapeutic efficacy immune checkpoint inhibitors (ICIs) monotherapy in NSCLC.We retrospectively enrolled 112 stage IIIB-IV NSCLC receiving ICIs monotherapy.The random forest (RF) algorithm used establish prediction models based on five...
Abstract Background Immunotherapy has improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), but only a small subset achieved clinical benefit. The purpose our study was to integrate multidimensional data using machine learning method predict therapeutic efficacy immune checkpoint inhibitors (ICIs) monotherapy in NSCLC. Methods We retrospectively enrolled 112 stage IIIB-IV NSCLC receiving ICIs monotherapy. random forest (RF) algorithm used establish prediction...