Benjamin S. Glicksberg
Orcid: 0000-0003-4515-8090
According to our database1,
Benjamin S. Glicksberg
authored at least 54 papers
between 2015 and 2024.
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Bibliography
2024
Generative Large Language Models are autonomous practitioners of evidence-based medicine.
CoRR, 2024
2023
Biomonitoring and precision health in deep space supported by artificial intelligence.
Nat. Mac. Intell., March, 2023
Biological research and self-driving labs in deep space supported by artificial intelligence.
Nat. Mac. Intell., March, 2023
Frontiers Artif. Intell., February, 2023
A foundational vision transformer improves diagnostic performance for electrocardiograms.
npj Digit. Medicine, 2023
Generation of a Compendium of Transcription Factor Cascades and Identification of Potential Therapeutic Targets using Graph Machine Learning.
CoRR, 2023
Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn).
Proceedings of the Machine Learning for Healthcare Conference, 2023
Optimizing Embedding Space with Sub-categorical Supervised Pre-training: A Theoretical Approach Towards Improving Sepsis Prediction.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023
2022
Autoencoders for sample size estimation for fully connected neural network classifiers.
npj Digit. Medicine, 2022
HeartBEiT: Vision Transformer for Electrocardiogram Data Improves Diagnostic Performance at Low Sample Sizes.
CoRR, 2022
Knowledge-Augmented Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022
Predicting Age-related Macular Degeneration Progression with Longitudinal Fundus Images Using Deep Learning.
Proceedings of the Machine Learning in Medical Imaging - 13th International Workshop, 2022
Supervised pretraining through contrastive categorical positive samplings to improve COVID-19 mortality prediction.
Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022
Defining an Ethical Relationship with Artificial Intelligence at a Large Academic Health System.
Proceedings of the AMIA 2022, 2022
2021
Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit.
IEEE Trans. Big Data, 2021
Patterns, 2021
Phe2vec: Automated disease phenotyping based on unsupervised embeddings from electronic health records.
Patterns, 2021
Extracting social determinants of health from electronic health records using natural language processing: a systematic review.
J. Am. Medical Informatics Assoc., 2021
Predictive Modelling of Susceptibility to Substance Abuse, Mortality and Drug-Drug Interactions in Opioid Patients.
Frontiers Artif. Intell., 2021
Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records.
Data Intell., 2021
Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs.
CoRR, 2021
Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health.
CoRR, 2021
Cross-Modal Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop.
CoRR, 2021
Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data.
CoRR, 2021
CoRR, 2021
A Simple Free-Text-like Method for Extracting Semi-Structured Data from Electronic Health Records: Exemplified in Prediction of In-Hospital Mortality.
Big Data Cogn. Comput., 2021
Multi-Modal Data Science for Healthcare: State of the Art, Challenges, and Opportunities.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
Extracting Social Isolation Information From Psychiatric Notes in the Electronic Health Records.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
2020
Protected Health Information filter (Philter): accurately and securely de-identifying free-text clinical notes.
npj Digit. Medicine, 2020
Deep representation learning of electronic health records to unlock patient stratification at scale.
npj Digit. Medicine, 2020
Identification of therapeutic targets from genetic association studies using hierarchical component analysis.
BioData Min., 2020
Sepsis in the era of data-driven medicine: personalizing risks, diagnoses, treatments and prognoses.
Briefings Bioinform., 2020
Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions.
Proceedings of the Artificial Intelligence in Medicine, 2020
2019
Deep learning predicts hip fracture using confounding patient and healthcare variables.
npj Digit. Medicine, 2019
PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model.
Bioinform., 2019
CANDI: an R package and Shiny app for annotating radiographs and evaluating computer-aided diagnosis.
Bioinform., 2019
Evaluation of patient re-identification using laboratory test orders and mitigation via latent space variables.
Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019
2018
Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining.
BMC Medical Informatics Decis. Mak., 2018
Time Aggregation and Model Interpretation for Deep Multivariate Longitudinal Patient Outcome Forecasting Systems in Chronic Ambulatory Care.
CoRR, 2018
Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning.
Briefings Bioinform., 2018
Loss-of-function of neuroplasticity-related genes confers risk for human neurodevelopmental disorders.
Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018
Causal inference on electronic health records to assess blood pressure treatment targets: An application of the parametric g formula.
Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018
Automated disease cohort selection using word embeddings from Electronic Health Records.
Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018
Proceedings of the 12th EAI International Conference on Pervasive Computing Technologies for Healthcare, 2018
2017
Predicting age by mining electronic medical records with deep learning characterizes differences between chronological and physiological age.
J. Biomed. Informatics, 2017
Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams.
Briefings Bioinform., 2017
Identify Cancer Driver Genes Through Shared Mendelian Disease Pathogenic Variants and Cancer Somatic Mutations.
Proceedings of the Biocomputing 2017: Proceedings of the Pacific Symposium, 2017
2016
Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networks.
Bioinform., 2016
2015
Proceedings of the Biocomputing 2015: Proceedings of the Pacific Symposium, 2015