B. Ru

发表

Identifying Serendipitous Drug Usages in Patient Forum Data - A Feasibility Study

Yong Ge, Boshu Ru, Lixia Yao, 2017, HEALTHINF.

A Literature Review of Social Media-Based Data Mining for Health Outcomes Research

B. Ru, Lixia Yao, 2019, Social Web and Health Research.

IDENTIFYING SERENDIPITOUS DRUG USAGES FROM PATIENT-REPORTED MEDICATION OUTCOMES ON SOCIAL MEDIA

B. Ru, Lixia Yao, M. Hadzikadic, 2018 .

Improving preeclampsia risk prediction by modeling pregnancy trajectories from routinely collected electronic medical record data

Siobhan M. Dolan, B. Ru, E. Schadt, 2022, npj Digital Medicine.

Serendipity—A Machine-Learning Application for Mining Serendipitous Drug Usage From Social Media

Dingcheng Li, Yueqi Hu, Boshu Ru, 2019, IEEE Transactions on NanoBioscience.

Detecting Serendipitous Drug Usage in Social Media with Deep Neural Network Models

Dingcheng Li, Boshu Ru, Lixia Yao, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

A Content Analysis of Patient-Reported Medication Outcomes on Social Media

Boshu Ru, Kimberly Harris, Lixia Yao, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

Dose Prediction for Prostate Radiation Treatment: Feasibility of a Distance-Based Deep Learning Model

Mirsad Hadzikadic, Yaorong Ge, Boshu Ru, 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

PCN37 An Oncology Real-World Data Assessment Framework for Outcomes Research

B. Ru, H. Estiri, S. Chandwani, 2021 .

An Empirical Study of Using An Ensemble Model in e-Commerce Taxonomy Classification Challenge

Xin Wang, Hanqing Cao, Yugang Jia, 2018, eCOM@SIGIR.

A Machine Learning Approach to Real‐World Time to Treatment Discontinuation Prediction

B. Ru, Y. Guan, Weilin Meng, 2023, Adv. Intell. Syst..

Comparison of Machine Learning Algorithms for Predicting Hospital Readmissions and Worsening Heart Failure Events in Patients With Heart Failure With Reduced Ejection Fraction: Modeling Study

B. Ru, D. Lautsch, Xi Tan, 2023, JMIR formative research.

Predicting Measles Outbreaks in the United States: Evaluation of Machine Learning Approaches

B. Ru, M. Pawaskar, S. Kujawski, 2022, JMIR formative research.

Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction

Justin L. Vincent, B. Ru, Lingfeng Yang, 2021, Journal of health economics and outcomes research.

Evaluation of the informatician perspective: determining types of research papers preferred by clinicians

Xiaoyan Wang, Boshu Ru, Lixia Yao, 2017, BMC Medical Informatics and Decision Making.

Prediction of measles cases in US counties: A machine learning approach.

B. Ru, M. Pawaskar, N. Afanador, 2024, Vaccine.