Chaohe Zhang
YOU?
Author Swipe
View article: Predict and Interpret Health Risk using EHR through Typical Patients
Predict and Interpret Health Risk using EHR through Typical Patients Open
Predicting health risks from electronic health records (EHR) is a topic of recent interest. Deep learning models have achieved success by modeling temporal and feature interaction. However, these methods learn insufficient representations …
View article: Mortality prediction with adaptive feature importance recalibration for peritoneal dialysis patients
Mortality prediction with adaptive feature importance recalibration for peritoneal dialysis patients Open
View article: Domain-invariant Clinical Representation Learning by Bridging Data Distribution Shift across EMR Datasets
Domain-invariant Clinical Representation Learning by Bridging Data Distribution Shift across EMR Datasets Open
Emerging diseases present challenges in symptom recognition and timely clinical intervention due to limited available information. An effective prognostic model could assist physicians in making accurate diagnoses and designing personalize…
View article: VecoCare: Visit Sequences-Clinical Notes Joint Learning for Diagnosis Prediction in Healthcare Data
VecoCare: Visit Sequences-Clinical Notes Joint Learning for Diagnosis Prediction in Healthcare Data Open
Due to the insufficiency of electronic health records (EHR) data utilized in practical diagnosis prediction scenarios, most works are devoted to learning powerful patient representations either from structured EHR data (e.g., temporal medi…
View article: Mortality Prediction with Adaptive Feature Importance Recalibration for Peritoneal Dialysis Patients: a deep-learning-based study on a real-world longitudinal follow-up dataset
Mortality Prediction with Adaptive Feature Importance Recalibration for Peritoneal Dialysis Patients: a deep-learning-based study on a real-world longitudinal follow-up dataset Open
Objective: Peritoneal Dialysis (PD) is one of the most widely used life-supporting therapies for patients with End-Stage Renal Disease (ESRD). Predicting mortality risk and identifying modifiable risk factors based on the Electronic Medica…
View article: See Clicks Differently: Modeling User Clicking Alternatively with Multi Classifiers for CTR Prediction
See Clicks Differently: Modeling User Clicking Alternatively with Multi Classifiers for CTR Prediction Open
Many recommender systems optimize click through rates (CTRs) as one of their core goals, and it further breaks down to predicting each item's click probability for a user (user-item click probability) and recommending the top ones to this …
View article: M3Care: Learning with Missing Modalities in Multimodal Healthcare Data
M3Care: Learning with Missing Modalities in Multimodal Healthcare Data Open
Multimodal electronic health record (EHR) data are widely used in clinical\napplications. Conventional methods usually assume that each sample (patient) is\nassociated with the unified observed modalities, and all modalities are\navailable…
View article: Instability of standing waves for a quasi-linear Schrödinger equation in the critical case
Instability of standing waves for a quasi-linear Schrödinger equation in the critical case Open
We consider the following quasi-linear Schrödinger equation. \begin{document} $ \begin{align} i\frac{\partial\psi}{\partial t}+\triangle\psi+\psi\triangle|\psi|^2+|\psi|^{p-1}\psi = 0,x\in \mathbb{R}^D, D\geq1, \;\;\;\;\;\;\;\;\…
View article: GRASP: Generic Framework for Health Status Representation Learning Based on Incorporating Knowledge from Similar Patients
GRASP: Generic Framework for Health Status Representation Learning Based on Incorporating Knowledge from Similar Patients Open
Deep learning models have been applied to many healthcare tasks based on electronic medical records (EMR) data and shown substantial performance. Existing methods commonly embed the records of a single patient into a representation for med…
View article: ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context
ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context Open
Predicting the patient's clinical outcome from the historical electronic medical records (EMR) is a fundamental research problem in medical informatics. Most deep learning-based solutions for EMR analysis concentrate on learning the clinic…
View article: Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach
Estimating Urban Road GPS Environment Friendliness with Bus Trajectories: A City-Scale Approach Open
GPS is taken as the most prevalent positioning system in practice. However, in urban areas, as the GPS satellite signal could be blocked by buildings, the GPS positioning is not accurate due to multi-path errors. Estimating the negative im…
View article: ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context
ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context Open
Predicting the patient's clinical outcome from the historical electronic medical records (EMR) is a fundamental research problem in medical informatics. Most deep learning-based solutions for EMR analysis concentrate on learning the clinic…