Majid Afshar
Orcid: 0000-0002-6368-4652
According to our database1,
Majid Afshar
authored at least 47 papers
between 2018 and 2024.
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Bibliography
2024
On the role of the UMLS in supporting diagnosis generation proposed by Large Language Models.
J. Biomed. Informatics, 2024
Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models.
J. Am. Medical Informatics Assoc., 2024
Development and external validation of deep learning clinical prediction models using variable-length time series data.
J. Am. Medical Informatics Assoc., 2024
Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review.
CoRR, 2024
Lessons Learned on Information Retrieval in Electronic Health Records: A Comparison of Embedding Models and Pooling Strategies.
CoRR, 2024
When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
CoRR, 2024
Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data.
CoRR, 2024
When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
2023
Improving model transferability for clinical note section classification models using continued pretraining.
J. Am. Medical Informatics Assoc., December, 2023
Progress Note Understanding - Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 shared task.
J. Biomed. Informatics, June, 2023
J. Biomed. Informatics, February, 2023
Considerations for health care institutions training large language models on electronic health records.
CoRR, 2023
Leveraging A Medical Knowledge Graph into Large Language Models for Diagnosis Prediction.
CoRR, 2023
Overview of the Problem List Summarization (ProbSum) 2023 Shared Task on Summarizing Patients' Active Diagnoses and Problems from Electronic Health Record Progress Notes.
CoRR, 2023
Progress Note Understanding - Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 Shared Task.
CoRR, 2023
Overview of the Problem List Summarization (ProbSum) 2023 Shared Task on Summarizing Patients' Active Diagnoses and Problems from Electronic Health Record Progress Notes.
Proceedings of the 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, 2023
Improving the Transferability of Clinical Note Section Classification Models with BERT and Large Language Model Ensembles.
Proceedings of the 5th Clinical Natural Language Processing Workshop, 2023
Proceedings of the 5th Clinical Natural Language Processing Workshop, 2023
2022
A scoping review of publicly available language tasks in clinical natural language processing.
J. Am. Medical Informatics Assoc., 2022
J. Am. Medical Informatics Assoc., 2022
Image and structured data analysis for prognostication of health outcomes in patients presenting to the ED during the COVID-19 pandemic.
Int. J. Medical Informatics, 2022
Governance of Clinical AI applications to facilitate safe and equitable deployment in a large health system: Key elements and early successes.
Frontiers Digit. Health, 2022
Optimizing feature selection methods by removing irrelevant features using sparse least squares.
Expert Syst. Appl., 2022
Summarizing Patients Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models.
CoRR, 2022
Hierarchical Annotation for Building A Suite of Clinical Natural Language Processing Tasks: Progress Note Understanding.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022
Summarizing Patients' Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models.
Proceedings of the 29th International Conference on Computational Linguistics, 2022
Explaining Alerts from a Pediatric Deterioration Prediction Model Using Clinical Text.
Proceedings of the AMIA 2022, 2022
2021
Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups.
J. Am. Medical Informatics Assoc., 2021
Incorporating Behavior in Attribute Based Access Control Model Using Machine Learning.
Proceedings of the IEEE International Systems Conference, 2021
The Addition of United States Census-Tract Data Does Not Improve the Prediction of Substance Misuse.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
A multi-label classifier to screen different types of substance misuse in hospitalized patients.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
Bias Assessment and Correction in Machine Learning Algorithms: A Use-Case in a Natural Language Processing Algorithm to Identify Hospitalized Patients with Unhealthy Alcohol Use.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
2020
Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients.
BMC Medical Informatics Decis. Mak., 2020
Proceedings of the AMIA 2020, 2020
2019
Canadian Wetland Inventory using Google Earth Engine: The First Map and Preliminary Results.
Remote. Sens., 2019
Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse.
J. Am. Medical Informatics Assoc., 2019
Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation.
J. Am. Medical Informatics Assoc., 2019
Development and application of a high throughput natural language processing architecture to convert all clinical documents in a clinical data warehouse into standardized medical vocabularies.
J. Am. Medical Informatics Assoc., 2019
Proceedings of the AMIA 2019, 2019
Proceedings of the AMIA 2019, 2019
Towards a Universal Document-Level Clinical Text Encoder: Methods for Neural Network Pre-training with Applications to Substance Misuse.
Proceedings of the AMIA 2019, 2019
2018
A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.
Proceedings of the AMIA 2018, 2018