Search Results for author: Kexin Huang

Found 16 papers, 10 papers with code

Machine Learning Applications for Therapeutic Tasks with Genomics Data

no code implementations3 May 2021 Kexin Huang, Cao Xiao, Lucas M. Glass, Cathy W. Critchlow, Greg Gibson, Jimeng Sun

Thanks to the increasing availability of genomics and other biomedical data, many machine learning approaches have been proposed for a wide range of therapeutic discovery and development tasks.

Graph Representation Learning in Biomedicine

no code implementations11 Apr 2021 Michelle M. Li, Kexin Huang, Marinka Zitnik

Biomedical networks are universal descriptors of systems of interacting elements, from protein interactions to disease networks, all the way to healthcare systems and scientific knowledge.

Graph Representation Learning

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development

2 code implementations18 Feb 2021 Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik

Here, we introduce Therapeutics Data Commons (TDC), the first unifying platform to systematically access and evaluate machine learning across the entire range of therapeutics.

Drug Discovery

HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data

1 code implementation8 Feb 2021 Tianfan Fu, Kexin Huang, Cao Xiao, Lucas M. Glass, Jimeng Sun

Next, these embeddings will be fed into the knowledge embedding module to generate knowledge embeddings that are pretrained using external knowledge on pharmaco-kinetic properties and trial risk from the web.

Imputation

An Interpretable End-to-end Fine-tuning Approach for Long Clinical Text

no code implementations12 Nov 2020 Kexin Huang, Sankeerth Garapati, Alexander S. Rich

Unstructured clinical text in EHRs contains crucial information for applications including decision support, trial matching, and retrospective research.

Text Classification

MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning

1 code implementation5 Oct 2020 Kexin Huang, Tianfan Fu, Dawood Khan, Ali Abid, Ali Abdalla, Abubakar Abid, Lucas M. Glass, Marinka Zitnik, Cao Xiao, Jimeng Sun

The efficacy of a drug depends on its binding affinity to the therapeutic target and pharmacokinetics.

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization

1 code implementation4 Oct 2020 Yue Yu, Kexin Huang, Chao Zhang, Lucas M. Glass, Jimeng Sun, Cao Xiao

Furthermore, most previous works focus on binary DDI prediction whereas the multi-typed DDI pharmacological effect prediction is a more meaningful but harder task.

Knowledge Graphs

Graph Meta Learning via Local Subgraphs

no code implementations NeurIPS 2020 Kexin Huang, Marinka Zitnik

G-Meta learns how to quickly adapt to a new task using only a handful of nodes or edges in the new task and does so by learning from data points in other graphs or related, albeit disjoint label sets.

Few-Shot Learning

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks

1 code implementation30 Apr 2020 Kexin Huang, Cao Xiao, Lucas Glass, Marinka Zitnik, Jimeng Sun

Here, we present SkipGNN, a graph neural network approach for the prediction of molecular interactions.

MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction

1 code implementation23 Apr 2020 Kexin Huang, Cao Xiao, Lucas Glass, Jimeng Sun

Drug target interaction (DTI) prediction is a foundational task for in silico drug discovery, which is costly and time-consuming due to the need of experimental search over large drug compound space.

Drug Discovery Representation Learning

ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission

2 code implementations10 Apr 2019 Kexin Huang, Jaan Altosaar, Rajesh Ranganath

Clinical notes contain information about patients that goes beyond structured data like lab values and medications.

Readmission Prediction

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