World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
11429
World Ranking
5565
National Ranking
2543

Overview

Chunhua Weng is affiliated with Columbia University in the United States. Their research spans fields within biochemistry, genetics, molecular biology, and medicine, with a specific focus on artificial intelligence, genetics, molecular biology, public health, and econometrics. The scientist's work integrates interdisciplinary approaches involving computational methods and biomedical sciences.

Their research topics include:

  • Biomedical Text Mining and Ontologies
  • Topic Modeling
  • Machine Learning in Healthcare
  • Genomics and Rare Diseases
  • Genetic Associations and Epidemiology
  • Ethics in Clinical Research
  • Artificial Intelligence in Healthcare and Education

They have published extensively in several prominent venues, including:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of the American Medical Informatics Association
  • Journal of Biomedical Informatics
  • Studies in Health Technology and Informatics
  • arXiv (Cornell University)

Frequent co-authors collaborating with Chunhua Weng are:

  • Cong Liu
  • Wendy K. Chung
  • Casey Ta
  • George Hripcsak
  • Wei-Qi Wei

Among recent publications, notable works include:

  • "Evaluating large language models on medical evidence summarization," 2023, npj Digital Medicine
  • "Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations," 2024, Nature Medicine
  • "Genome-wide polygenic score to predict chronic kidney disease across ancestries," 2022, Nature Medicine
  • "Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations," 2020, npj Digital Medicine
  • "Factors Affecting the Quality of Person-Generated Wearable Device Data and Associated Challenges: Rapid Systematic Review," 2021, JMIR mhealth and uhealth

Chunhua Weng's work frequently intersects computational and clinical domains. Their research on polygenic risk scores and genome-wide prediction models targets diverse populations, reflecting an emphasis on genetic epidemiology and precision medicine.

Their studies on large language models for medical evidence summarization and wearable device data quality further illustrate a focus on leveraging artificial intelligence and big data for healthcare applications. The scientist's contributions encompass the development and evaluation of methodologies relevant to machine learning in healthcare and the implementation of evidence-based clinical tools.

Best Publications

  • Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research.

    Nicole Gray Weiskopf;Chunhua Weng

  • Diagnostic Utility of Exome Sequencing for Kidney Disease

    Emily E Groopman;Maddalena Marasa;Sophia Cameron-Christie;Slavé Petrovski

  • A Harmonized Data Quality Assessment Terminology and Framework for the Secondary Use of Electronic Health Record Data

    Michael G. Kahn;Tiffany J. Callahan;Juliana Barnard;Alan E. Bauck

  • Secondary Use of EHR: Data Quality Issues and Informatics Opportunities.

    Taxiarchis Botsis;Gunnar Hartvigsen;Fei Chen;Chunhua Weng

  • Defining and measuring completeness of electronic health records for secondary use

    Nicole G. Weiskopf;George Hripcsak;Sushmita Swaminathan;Chunhua Weng

  • Evaluating large language models on medical evidence summarization

    Unknown

  • Formal representation of eligibility criteria

    Chunhua Weng;Samson W. Tu;Ida Sim;Rachel Richesson

  • Electronic Screening Improves Efficiency in Clinical Trial Recruitment

    Samir R. Thadani;Samir R. Thadani;Chunhua Weng;J. Thomas Bigger;John F. Ennever

  • EliXR: an approach to eligibility criteria extraction and representation

    Chunhua Weng;Xiaoying Wu;Zhihui Luo;Mary Regina Boland

  • Combining PubMed knowledge and EHR data to develop a weighted bayesian network for pancreatic cancer prediction

    Di Zhao;Chunhua Weng

  • Criteria2Query: a natural language interface to clinical databases for cohort definition

    Chi Yuan;Chi Yuan;Patrick B. Ryan;Patrick B. Ryan;Casey N. Ta;Yixuan Guo

  • A Data Quality Assessment Guideline for Electronic Health Record Data Reuse.

    Nicole G. Weiskopf;Suzanne Bakken;George Hripcsak;Chunhua Weng

  • Hidden in plain sight: bias towards sick patients when sampling patients with sufficient electronic health record data for research

    Alexander Rusanov;Nicole Gray Weiskopf;Shuang Wang;Chunhua Weng

  • A review of auditing methods applied to the content of controlled biomedical terminologies

    Xinxin Zhu;Jung-Wei Fan;David M. Baorto;Chunhua Weng

  • Deep Phenotyping on Electronic Health Records Facilitates Genetic Diagnosis by Clinical Exomes

    Jung Hoon Son;Gangcai Xie;Chi Yuan;Lyudmila Ena

  • Translating Evidence Into Practice: Eligibility Criteria Fail to Eliminate Clinically Significant Differences Between Real-World and Study Populations

    Amelia J. Averitt;Chunhua Weng;Patrick Ryan;Patrick Ryan;Adler Perotte

  • Asynchronous collaborative writing through annotations

    Chunhua Weng;John H. Gennari

  • EliIE: An open-source information extraction system for clinical trial eligibility criteria.

    Tian Kang;Shaodian Zhang;Youlan Tang;Gregory William Hruby

  • Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials

    Riccardo Miotto;Chunhua Weng

  • Sick patients have more data: the non-random completeness of electronic health records.

    Nicole Gray Weiskopf;Alex Rusanov;Chunhua Weng

  • Using EHRs to integrate research with patient care: promises and challenges.

    Chunhua Weng;Paul Appelbaum;George Hripcsak;Ian Kronish

  • Comparing ICD9-encoded diagnoses and NLP-processed discharge summaries for clinical trials pre-screening: a case study.

    Li Li;Herbert S. Chase;Chintan O. Patel;Carol Friedman

Frequent Co-Authors

George Hripcsak
George Hripcsak Columbia University
Wendy K. Chung
Wendy K. Chung Columbia University
Hakon Hakonarson
Hakon Hakonarson Children's Hospital of Philadelphia
Gail P. Jarvik
Gail P. Jarvik University of Washington
Suzanne Bakken
Suzanne Bakken Columbia University
Kai Wang
Kai Wang Hebei University
James J. Cimino
James J. Cimino University of Alabama at Birmingham
Joshua C. Denny
Joshua C. Denny National Institutes of Health
John H. Gennari
John H. Gennari University of Washington
Christopher G. Chute
Christopher G. Chute Johns Hopkins University

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