Implementation of Deep Patient Representation of Clinical Notes at Intensive Care Unit for Multi-Task Prediction
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Updated
Jul 26, 2019 - Python
Implementation of Deep Patient Representation of Clinical Notes at Intensive Care Unit for Multi-Task Prediction
BERT for TCM clinical records classification. JAMIA 2019
multilabel classification of EHR notes
Vocabulary-based detection of fall events in Dutch clinical notes.
Research Practical and Master Thesis topic for the University of Luxembourg. Natural language processing pipeline to extract HPO terms from clinical notes or EHR, annotate genes and diseases to the extracted terms and prioritize them by their frequency.
Code and Datasets for the paper "TransICD: Transformer Based Code-wise Attention Model for Explainable ICD Coding", accepted by AIME 2021.
Extracting Patients' information from clinical notes and export them to an OMOP CDM database.
MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain (ACL-IJCNLP '21)
Deep learning for cancer symptoms monitoring on the basis of EHR unstructured clinical notes
A Multimodal Transformer: Fusing Clinical Notes With Structured EHR Data for Interpretable In-Hospital Mortality Prediction
Repository of FHIR and annotation resources used to benchmark NLP Sandbox tools
Rare disease identification from free-text clinical notes with ontologies and weak supervision
MEDIQA-Chat Shared Tasks @ ACL-ClinicalNLP 2023
Uses Whisper AI to transcribe and process audio files, with the output being useful to psychotherapists.
📰 High-performance tool for negation and uncertainty detection in radiology reports
Estimate sentiment in clinical notes via keywords or deep learning models
A tool for automatically labelling discharge summaries into disease categories.
GPTNERMED is a language model-generated, synthetic dataset and an open neural NER model for medical entities designed for German data.
GERNERMED is the first open neural NER model for medical entities designed for German data.
GERNERMED++ is a transfer-learning-based open neural NER model for medical entities designed for German data.
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