Hao Liu

Orcid: 0000-0002-1975-1272

Affiliations:

Montclair State University, NJ, USA
Columbia University, Department of Biomedical Informatics, New York, USA (former)
New Jersey Institute of Technology, NJ, USA (PhD 2020)

According to our database¹, Hao Liu authored at least 39 papers between 2019 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Audiovisual Multimodal Cough Data Analysis for Tuberculosis Detection.

[BibT_eX]

[DOI]

Proceedings of the 15th International Conference on Information, 2024

2023

The suitability of UMLS and SNOMED-CT for encoding outcome concepts.

[BibT_eX]

[DOI]

J. Am. Medical Informatics Assoc., November, 2023

A data-driven approach to optimizing clinical study eligibility criteria.

[BibT_eX]

[DOI]

J. Biomed. Informatics, June, 2023

How Good Is ChatGPT for Medication Evidence Synthesis?

[BibT_eX]

[DOI]

Hao Liu

Yifan Peng

Chunhua Weng

Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023

2022

Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks.

[BibT_eX]

[DOI]

Dataset, December, 2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network.

[BibT_eX]

[DOI]

Dataset, June, 2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network.

[BibT_eX]

[DOI]

Dataset, June, 2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network.

[BibT_eX]

[DOI]

Dataset, June, 2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network.

[BibT_eX]

[DOI]

Dataset, June, 2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network.

[BibT_eX]

[DOI]

Dataset, June, 2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network.

[BibT_eX]

[DOI]

Dataset, June, 2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network.

[BibT_eX]

[DOI]

Dataset, June, 2022

Ontology-based categorization of clinical studies by their conditions.

[BibT_eX]

[DOI]

J. Biomed. Informatics, 2022

Combining human and machine intelligence for clinical trial eligibility querying.

[BibT_eX]

[DOI]

J. Am. Medical Informatics Assoc., 2022

Data-Driven Modeling of Randomized Controlled Trial Outcomes.

[BibT_eX]

[DOI]

Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

Criteria2Query 2.0: Combining Machine Efficiency and Human Intelligence to Define a More Accurate and Feasible Cohort for Clinical Trial Recruitment.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2022, 2022

2021

Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks.

[BibT_eX]

[DOI]

Dataset, November, 2021

Predicting Solar Flares Using a Long Short-term Memory Network.

[BibT_eX]

[DOI]

Dataset, November, 2021

Predicting Solar Flares Using a Long Short-term Memory Network.

[BibT_eX]

[DOI]

Dataset, November, 2021

Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks.

[BibT_eX]

[DOI]

Dataset, November, 2021

Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning.

[BibT_eX]

[DOI]

Dataset, November, 2021

Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning.

[BibT_eX]

[DOI]

Dataset, October, 2021

Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning.

[BibT_eX]

[DOI]

Dataset, October, 2021

Building an OMOP common data model-compliant annotated corpus for COVID-19 clinical trials.

[BibT_eX]

[DOI]

Christopher T. Southard

Jae Hyun Kim

Chunhua Weng

J. Biomed. Informatics, 2021

A knowledge base of clinical trial eligibility criteria.

[BibT_eX]

[DOI]

J. Biomed. Informatics, 2021

The COVID-19 Trial Finder.

[BibT_eX]

[DOI]

J. Am. Medical Informatics Assoc., 2021

Towards clinical data-driven eligibility criteria optimization for interventional COVID-19 clinical trials.

[BibT_eX]

[DOI]

Mitchell S. V. Elkind

Chunhua Weng

J. Am. Medical Informatics Assoc., 2021

Misalignment between COVID-19 hotspots and clinical trial sites.

[BibT_eX]

[DOI]

Lauren Franks

Hao Liu

Mitchell S. V. Elkind

Muredach P. Reilly

Chunhua Weng

Shing M. Lee

J. Am. Medical Informatics Assoc., 2021

A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data.

[BibT_eX]

[DOI]

Appl. Clin. Inform., 2021

Participatory Design of a Clinical Trial Eligibility Criteria Simplification Method.

[BibT_eX]

[DOI]

Proceedings of the Public Health and Informatics, 2021

Potential Role of Clinical Trial Eligibility Criteria in Electronic Phenotyping.

[BibT_eX]

[DOI]

Proceedings of the Public Health and Informatics, 2021

Extending PICO with Observation Normalization for Evidence Computing.

[BibT_eX]

[DOI]

Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021

Evaluation of Criteria2Query: Towards Augmented Intelligence for Cohort Identification.

[BibT_eX]

[DOI]

Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021

A Sample Size Extractor for RCT Reports.

[BibT_eX]

[DOI]

Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021

Representation and Normalization of Complex Interventions for Evidence Computing.

[BibT_eX]

[DOI]

Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021

2020

Potential Role of Clinical Trial Eligibility Criteria in Electronic Phenotyping.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2020, 2020

2019

Prism2/LSTM-flare-prediction: v1.0.1.

[BibT_eX]

[DOI]

Dataset, June, 2019

Predicting Solar Flares Using a Long Short-term Memory Network.

[BibT_eX]

[DOI]

Dataset, June, 2019

Predicting Solar Flares Using a Long Short-term Memory Network.

[BibT_eX]

[DOI]

Dataset, June, 2019

Hao Liu

Timeline

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