Search Results for author: Jimeng Sun

Found 82 papers, 39 papers with code

Self-supervised EEG Representation Learning for Automatic Sleep Staging

1 code implementation27 Oct 2021 Chaoqi Yang, Danica Xiao, M. Brandon Westover, Jimeng Sun

Objective: In this paper, we aim to learn robust vector representations from massive unlabeled Electroencephalogram (EEG) signals, such that the learned representations (1) are expressive enough to replace the raw signals in the sleep staging task; and (2) provide better predictive performance than supervised models in scenarios of fewer labels and noisy samples.

EEG Representation Learning +2

SurvTRACE: Transformers for Survival Analysis with Competing Events

1 code implementation2 Oct 2021 Zifeng Wang, Jimeng Sun

In medicine, survival analysis studies the time duration to events of interest such as mortality.

Multi-Task Learning Selection bias +1

PAC-Bayes Information Bottleneck

1 code implementation29 Sep 2021 Zifeng Wang, Shao-Lun Huang, Ercan E. Kuruoglu, Jimeng Sun, Xi Chen, Yefeng Zheng

In this work, we build a new IB based on the trade-off between the accuracy and complexity of learned weights of NNs.

Differentiable Scaffolding Tree for Molecular Optimization

no code implementations22 Sep 2021 Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, Jimeng Sun

The structural design of functional molecules, also called molecular optimization, is an essential chemical science and engineering task with important applications, such as drug discovery.

Combinatorial Optimization Drug Discovery

Augmented Tensor Decomposition with Stochastic Optimization

no code implementations15 Jun 2021 Chaoqi Yang, Cheng Qian, Navjot Singh, Cao Xiao, M Brandon Westover, Edgar Solomonik, Jimeng Sun

Tensor decompositions are powerful tools for dimensionality reduction and feature interpretation of multidimensional data such as signals.

Data Augmentation Dimensionality Reduction +2

MTC: Multiresolution Tensor Completion from Partial and Coarse Observations

1 code implementation14 Jun 2021 Chaoqi Yang, Navjot Singh, Cao Xiao, Cheng Qian, Edgar Solomonik, Jimeng Sun

Our MTC model explores tensor mode properties and leverages the hierarchy of resolutions to recursively initialize an optimization setup, and optimizes on the coupled system using alternating least squares.

Locally Valid and Discriminative Prediction Intervals for Deep Learning Models

1 code implementation NeurIPS 2021 Zhen Lin, Shubhendu Trivedi, Jimeng Sun

Moreover, when combined with deep learning (DL) methods, it should be scalable and affect the DL model performance minimally.

Prediction Intervals

Multi-version Tensor Completion for Time-delayed Spatio-temporal Data

no code implementations11 May 2021 Cheng Qian, Nikos Kargas, Cao Xiao, Lucas Glass, Nicholas Sidiropoulos, Jimeng Sun

Recovering such missing or noisy (under-reported) elements of the input tensor can be viewed as a generalized tensor completion problem.

Missing Elements

SafeDrug: Dual Molecular Graph Encoders for Safe Drug Recommendations

1 code implementation5 May 2021 Chaoqi Yang, Cao Xiao, Fenglong Ma, Lucas Glass, Jimeng Sun

On a benchmark dataset, our SafeDrug is relatively shown to reduce DDI by 19. 43% and improves 2. 88% on Jaccard similarity between recommended and actually prescribed drug combinations over previous approaches.

Change Matters: Medication Change Prediction with Recurrent Residual Networks

no code implementations5 May 2021 Chaoqi Yang, Cao Xiao, Lucas Glass, Jimeng Sun

Deep learning is revolutionizing predictive healthcare, including recommending medications to patients with complex health conditions.

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.

SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models

no code implementations5 Mar 2021 Zhen Lin, Cao Xiao, Lucas Glass, M. Brandon Westover, Jimeng Sun

Despite deep learning (DL) success in classification problems, DL classifiers do not provide a sound mechanism to decide when to refrain from predicting.

Atrial Fibrillation Detection EEG +3

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

no code implementations8 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.


PyHealth: A Python Library for Health Predictive Models

2 code implementations11 Jan 2021 Yue Zhao, Zhi Qiao, Cao Xiao, Lucas Glass, Jimeng Sun

PyHealth consists of data preprocessing module, predictive modeling module, and evaluation module.

EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders

no code implementations18 Dec 2020 Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley Malin, Walter Stewart, Jimeng Sun

De-identified EHRs do not adequately address the needs of health systems, as de-identified data are susceptible to re-identification and its volume is also limited.

Variational Inference

STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization

no code implementations8 Dec 2020 Nikos Kargas, Cheng Qian, Nicholas D. Sidiropoulos, Cao Xiao, Lucas M. Glass, Jimeng Sun

Accurate prediction of the transmission of epidemic diseases such as COVID-19 is crucial for implementing effective mitigation measures.

FLANNEL: Focal Loss Based Neural Network Ensemble for COVID-19 Detection

no code implementations30 Oct 2020 Zhi Qiao, Austin Bae, Lucas M. Glass, Cao Xiao, Jimeng Sun

To test the possibility of differentiating chest x-ray images of COVID-19 against other pneumonia and healthy patients using deep neural networks.

UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data

no code implementations22 Oct 2020 Chacha Chen, Junjie Liang, Fenglong Ma, Lucas M. Glass, Jimeng Sun, Cao Xiao

However, existing uncertainty estimation approaches often failed in handling high-dimensional data, which are present in multi-sourced data.

Variational Inference

SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors

no code implementations8 Oct 2020 Ardavan Afshar, Kejing Yin, Sherry Yan, Cheng Qian, Joyce C. Ho, Haesun Park, Jimeng Sun

In particular, we define the N-th order tensor Wasserstein loss for the widely used tensor CP factorization and derive the optimization algorithm that minimizes it.

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.

MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization

no code implementations5 Oct 2020 Tianfan Fu, Cao Xiao, Xinhao Li, Lucas M. Glass, Jimeng Sun

Molecule optimization is a fundamental task for accelerating drug discovery, with the goal of generating new valid molecules that maximize multiple drug properties while maintaining similarity to the input molecule.

Drug Discovery Type prediction

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

SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates

2 code implementations ICML 2020 Lingkai Kong, Jimeng Sun, Chao Zhang

We propose a new method for quantifying uncertainties of DNNs from a dynamical system perspective.

HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units

1 code implementation10 Aug 2020 Shenda Hong, Yanbo Xu, Alind Khare, Satria Priambada, Kevin Maher, Alaa Aljiffry, Jimeng Sun, Alexey Tumanov

HOLMES is tested on risk prediction task on pediatric cardio ICU data with above 95% prediction accuracy and sub-second latency on 64-bed simulation.

EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision

no code implementations10 Jul 2020 Siddharth Biswal, Peiye Zhuang, Ayis Pyrros, Nasir Siddiqui, Sanmi Koyejo, Jimeng Sun

EMIXER is an conditional generative adversarial model by 1) generating an image based on a label, 2) encoding the image to a hidden embedding, 3) producing the corresponding text via a hierarchical decoder from the image embedding, and 4) a joint discriminator for assessing both the image and the corresponding text.

Data Augmentation Image Classification

ELF: An Early-Exiting Framework for Long-Tailed Classification

no code implementations22 Jun 2020 Rahul Duggal, Scott Freitas, Sunny Dhamnani, Duen Horng Chau, Jimeng Sun

The natural world often follows a long-tailed data distribution where only a few classes account for most of the examples.

General Classification

STEAM: Self-Supervised Taxonomy Expansion with Mini-Paths

1 code implementation18 Jun 2020 Yue Yu, Yinghao Li, Jiaming Shen, Hao Feng, Jimeng Sun, Chao Zhang

We propose a self-supervised taxonomy expansion model named STEAM, which leverages natural supervision in the existing taxonomy for expansion.

COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching

1 code implementation15 Jun 2020 Junyi Gao, Cao Xiao, Lucas M. Glass, Jimeng Sun

The other path processes EHR with multi-granularity memory network that encodes structured patient records into multiple levels based on medical ontology.

Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification

no code implementations15 Jun 2020 Rakshith S Srinivasa, Cao Xiao, Lucas Glass, Justin Romberg, Jimeng Sun

The attention mechanism has demonstrated superior performance for inference over nodes in graph neural networks (GNNs), however, they result in a high computational burden during both training and inference.

Graph Attention Node Classification

CHEER: Rich Model Helps Poor Model via Knowledge Infusion

no code implementations21 May 2020 Cao Xiao, Trong Nghia Hoang, Shenda Hong, Tengfei Ma, Jimeng Sun

There is a growing interest in applying deep learning (DL) to healthcare, driven by the availability of data with multiple feature channels in rich-data environments (e. g., intensive care units).

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

SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection

1 code implementation11 Mar 2020 Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Changlin Wan, Wen Wang, Jianing Yang, Haoping Bai, Zheng Li, Cao Xiao, Yunlong Wang, Zhi Qiao, Jimeng Sun, Leman Akoglu

Outlier detection (OD) is a key machine learning (ML) task for identifying abnormal objects from general samples with numerous high-stake applications including fraud detection and intrusion detection.

Dimensionality Reduction Fraud Detection +2

CLARA: Clinical Report Auto-completion

no code implementations26 Feb 2020 Siddharth Biswal, Cao Xiao, Lucas M. Glass, M. Brandon Westover, Jimeng Sun

Most existing methods try to generate the whole reports from the raw input with limited success because 1) generated reports often contain errors that need manual review and correction, 2) it does not save time when doctors want to write additional information into the report, and 3) the generated reports are not customized based on individual doctors' preference.


REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild

1 code implementation29 Jan 2020 Rahul Duggal, Scott Freitas, Cao Xiao, Duen Horng Chau, Jimeng Sun

By deploying these models to an Android application on a smartphone, we quantitatively observe that REST allows models to achieve up to 17x energy reduction and 9x faster inference.

EEG Neural Network Compression +1

StageNet: Stage-Aware Neural Networks for Health Risk Prediction

1 code implementation24 Jan 2020 Junyi Gao, Cao Xiao, Yasha Wang, Wen Tang, Lucas M. Glass, Jimeng Sun

Compared to the best baseline model, StageNet achieves up to 12% higher AUPRC for risk prediction task on two real-world patient datasets.

DeepEnroll: Patient-Trial Matching with Deep Embedding and Entailment Prediction

no code implementations22 Jan 2020 Xingyao Zhang, Cao Xiao, Lucas M. Glass, Jimeng Sun

To address these challenges, we proposed DeepEnroll, a cross-modal inference learning model to jointly encode enrollment criteria (text) and patients records (tabular data) into a shared latent space for matching inference.

Sentence Embedding

Opportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review

1 code implementation28 Dec 2019 Shenda Hong, Yuxi Zhou, Junyuan Shang, Cao Xiao, Jimeng Sun

Methods:We extracted papers that applied deep learning (deep neural network) models to ECG data that were published between Jan. 1st of 2010 and Feb. 29th of 2020 from Google Scholar, PubMed, and the DBLP.

Denoising Sleep Staging

CONAN: Complementary Pattern Augmentation for Rare Disease Detection

no code implementations26 Nov 2019 Limeng Cui, Siddharth Biswal, Lucas M. Glass, Greg Lever, Jimeng Sun, Cao Xiao

How to further leverage patients with possibly uncertain diagnosis to improve detection?

CORE: Automatic Molecule Optimization Using Copy & Refine Strategy

1 code implementation23 Nov 2019 Tianfan Fu, Cao Xiao, Jimeng Sun

The state-of-the-art approaches partition the molecules into a large set of substructures $S$ and grow the new molecule structure by iteratively predicting which substructure from $S$ to add.

Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment

no code implementations23 Nov 2019 Siddharth Biswal, Cao Xiao, Lucas M. Glass, Elizabeth Milkovits, Jimeng Sun

We propose doctor2vec which simultaneously learns 1) doctor representations from EHR data and 2) trial representations from the description and categorical information about the trials.

Representation Learning

CUP: Cluster Pruning for Compressing Deep Neural Networks

1 code implementation19 Nov 2019 Rahul Duggal, Cao Xiao, Richard Vuduc, Jimeng Sun

With CUP, we overcome two limitations of prior work-(1) non-uniform pruning: CUP can efficiently determine the ideal number of filters to prune in each layer of a neural network.

SLEEPER: interpretable Sleep staging via Prototypes from Expert Rules

no code implementations14 Oct 2019 Irfan Al-Hussaini, Cao Xiao, M. Brandon Westover, Jimeng Sun

In this study, we propose Sleep staging via Prototypes from Expert Rules (SLEEPER), which combines deep learning models with expert defined rules using a prototype learning framework to generate simple interpretable models.

Automatic Sleep Stage Classification Sleep Staging

GENN: Predicting Correlated Drug-drug Interactions with Graph Energy Neural Networks

no code implementations4 Oct 2019 Tengfei Ma, Junyuan Shang, Cao Xiao, Jimeng Sun

We propose the graph energy neural network (GENN) to explicitly model link type correlations.

Link Prediction

Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks

no code implementations1 Jul 2019 Kezi Yu, Yunlong Wang, Yong Cai, Cao Xiao, Emily Zhao, Lucas Glass, Jimeng Sun

Rare diseases affecting 350 million individuals are commonly associated with delay in diagnosis or misdiagnosis.

Predicting Treatment Initiation from Clinical Time Series Data via Graph-Augmented Time-Sensitive Model

no code implementations1 Jul 2019 Fan Zhang, Tong Wu, Yunlong Wang, Yong Cai, Cao Xiao, Emily Zhao, Lucas Glass, Jimeng Sun

Many computational models were proposed to extract temporal patterns from clinical time series for each patient and among patient group for predictive healthcare.

Time Series

Pre-training of Graph Augmented Transformers for Medication Recommendation

1 code implementation2 Jun 2019 Junyuan Shang, Tengfei Ma, Cao Xiao, Jimeng Sun

G-BERT is the first to bring the language model pre-training schema into the healthcare domain and it achieved state-of-the-art performance on the medication recommendation task.

Language Modelling Representation Learning +1

CGNF: Conditional Graph Neural Fields

no code implementations ICLR 2019 Tengfei Ma, Cao Xiao, Junyuan Shang, Jimeng Sun

By integrating the conditional random fields (CRF) in the graph convolutional networks, we explicitly model a joint probability of the entire set of node labels, thus taking advantage of neighborhood label information in the node label prediction task.

General Classification Node Classification

MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare

1 code implementation NeurIPS 2018 Edward Choi, Cao Xiao, Walter F. Stewart, Jimeng Sun

Deep learning models exhibit state-of-the-art performance for many predictive healthcare tasks using electronic health records (EHR) data, but these models typically require training data volume that exceeds the capacity of most healthcare systems.

Disease Prediction

AWE: Asymmetric Word Embedding for Textual Entailment

no code implementations11 Sep 2018 Tengfei Ma, Chiamin Wu, Cao Xiao, Jimeng Sun

It refers to the directional relation between text fragments such that the "premise" can infer "hypothesis".

Natural Language Inference Paraphrase Identification +2

RDPD: Rich Data Helps Poor Data via Imitation

1 code implementation6 Sep 2018 Shenda Hong, Cao Xiao, Trong Nghia Hoang, Tengfei Ma, Hongyan Li, Jimeng Sun

In many situations, we need to build and deploy separate models in related environments with different data qualities.

Knowledge Distillation

GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination

1 code implementation6 Sep 2018 Junyuan Shang, Cao Xiao, Tengfei Ma, Hongyan Li, Jimeng Sun

Recent progress in deep learning is revolutionizing the healthcare domain including providing solutions to medication recommendations, especially recommending medication combination for patients with complex health conditions.

RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data

no code implementations23 Jul 2018 Yanbo Xu, Siddharth Biswal, Shriprasad R Deshpande, Kevin O Maher, Jimeng Sun

With the improvement of medical data capturing, vast amount of continuous patient monitoring data, e. g., electrocardiogram (ECG), real-time vital signs and medications, become available for clinical decision support at intensive care units (ICUs).

RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records

no code implementations28 May 2018 Bum Chul Kwon, Min-Je Choi, Joanne Taery Kim, Edward Choi, Young Bin Kim, Soonwook Kwon, Jimeng Sun, Jaegul Choo

Therefore, our design study aims to provide a visual analytics solution to increase interpretability and interactivity of RNNs via a joint effort of medical experts, artificial intelligence scientists, and visual analytics researchers.

HAMLET: Interpretable Human And Machine co-LEarning Technique

no code implementations26 Mar 2018 Olivier Deiss, Siddharth Biswal, Jing Jin, Haoqi Sun, M. Brandon Westover, Jimeng Sun

Although cEEG monitoring yields large volumes of data, labeling costs and difficulty make it hard to build a classifier.

General Classification

COPA: Constrained PARAFAC2 for Sparse & Large Datasets

1 code implementation12 Mar 2018 Ardavan Afshar, Ioakeim Perros, Evangelos E. Papalexakis, Elizabeth Searles, Joyce Ho, Jimeng Sun

To tackle these challenges, we propose a {\it CO}nstrained {\it PA}RAFAC2 (COPA) method, which carefully incorporates optimization constraints such as temporal smoothness, sparsity, and non-negativity in the resulting factors.

Explainable Prediction of Medical Codes from Clinical Text

2 code implementations NAACL 2018 James Mullenbach, Sarah Wiegreffe, Jon Duke, Jimeng Sun, Jacob Eisenstein

Our method aggregates information across the document using a convolutional neural network, and uses an attention mechanism to select the most relevant segments for each of the thousands of possible codes.

Medical Code Prediction

SLEEPNET: Automated Sleep Staging System via Deep Learning

no code implementations26 Jul 2017 Siddharth Biswal, Joshua Kulas, Haoqi Sun, Balaji Goparaju, M. Brandon Westover, Matt T. Bianchi, Jimeng Sun

Sleep disorders, such as sleep apnea, parasomnias, and hypersomnia, affect 50-70 million adults in the United States (Hillman et al., 2006).

EEG Sleep Staging

Federated Tensor Factorization for Computational Phenotyping

no code implementations11 Apr 2017 Yejin Kim, Jimeng Sun, Hwanjo Yu, Xiaoqian Jiang

In this paper, we developed a novel solution to enable federated tensor factorization for computational phenotyping without sharing patient-level data.

Computational Phenotyping

Generating Multi-label Discrete Patient Records using Generative Adversarial Networks

3 code implementations19 Mar 2017 Edward Choi, Siddharth Biswal, Bradley Malin, Jon Duke, Walter F. Stewart, Jimeng Sun

Access to electronic health record (EHR) data has motivated computational advances in medical research.

SPARTan: Scalable PARAFAC2 for Large & Sparse Data

no code implementations13 Mar 2017 Ioakeim Perros, Evangelos E. Papalexakis, Fei Wang, Richard Vuduc, Elizabeth Searles, Michael Thompson, Jimeng Sun

For example, when modeling medical features across a set of patients, the number and duration of treatments may vary widely in time, meaning there is no meaningful way to align their clinical records across time points for analysis purposes.

Causal Regularization

no code implementations8 Feb 2017 Mohammad Taha Bahadori, Krzysztof Chalupka, Edward Choi, Robert Chen, Walter F. Stewart, Jimeng Sun

In application domains such as healthcare, we want accurate predictive models that are also causally interpretable.

Representation Learning

GRAM: Graph-based Attention Model for Healthcare Representation Learning

1 code implementation21 Nov 2016 Edward Choi, Mohammad Taha Bahadori, Le Song, Walter F. Stewart, Jimeng Sun

-Interpretation:The representations learned by deep learning methods should align with medical knowledge.

Representation Learning

Sparse Hierarchical Tucker Factorization and its Application to Healthcare

no code implementations25 Oct 2016 Ioakeim Perros, Robert Chen, Richard Vuduc, Jimeng Sun

It can also do so more accurately and in less time than the state-of-the-art: on a 12th order subset of the input data, Sparse H-Tucker is 18x more accurate and 7. 5x faster than a previously state-of-the-art method.

RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism

1 code implementation NeurIPS 2016 Edward Choi, Mohammad Taha Bahadori, Joshua A. Kulas, Andy Schuetz, Walter F. Stewart, Jimeng Sun

RETAIN was tested on a large health system EHR dataset with 14 million visits completed by 263K patients over an 8 year period and demonstrated predictive accuracy and computational scalability comparable to state-of-the-art methods such as RNN, and ease of interpretability comparable to traditional models.

Disease Trajectory Forecasting

FLASH: Fast Bayesian Optimization for Data Analytic Pipelines

1 code implementation20 Feb 2016 Yuyu Zhang, Mohammad Taha Bahadori, Hang Su, Jimeng Sun

To achieve the best performance, it is often critical to select optimal algorithms and to set appropriate hyperparameters, which requires large computational efforts.

Multi-layer Representation Learning for Medical Concepts

2 code implementations17 Feb 2016 Edward Choi, Mohammad Taha Bahadori, Elizabeth Searles, Catherine Coffey, Jimeng Sun

Learning efficient representations for concepts has been proven to be an important basis for many applications such as machine translation or document classification.

Document Classification Machine Translation +3

Medical Concept Representation Learning from Electronic Health Records and its Application on Heart Failure Prediction

1 code implementation11 Feb 2016 Edward Choi, Andy Schuetz, Walter F. Stewart, Jimeng Sun

Objective: To transform heterogeneous clinical data from electronic health records into clinically meaningful constructed features using data driven method that rely, in part, on temporal relations among data.

Representation Learning

Time-Sensitive Recommendation From Recurrent User Activities

no code implementations NeurIPS 2015 Nan Du, Yichen Wang, Niao He, Jimeng Sun, Le Song

By making personalized suggestions, a recommender system is playing a crucial role in improving the engagement of users in modern web-services.

Point Processes Recommendation Systems

Doctor AI: Predicting Clinical Events via Recurrent Neural Networks

1 code implementation18 Nov 2015 Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Jimeng Sun

Leveraging large historical data in electronic health record (EHR), we developed Doctor AI, a generic predictive model that covers observed medical conditions and medication uses.

Guaranteed Scalable Learning of Latent Tree Models

no code implementations18 Jun 2014 Furong Huang, Niranjan U. N., Ioakeim Perros, Robert Chen, Jimeng Sun, Anima Anandkumar

We present an integrated approach for structure and parameter estimation in latent tree graphical models.

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