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Cross-Modal self-supervised vision language pre-training with multiple objectives for medical visual question answering
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Sleep apnea test prediction based on Electronic Health Records
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MultiADE: A Multi-domain benchmark for Adverse Drug Event extraction
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Importance of variables from different time frames for predicting self-harm using health system data
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Early multi-cancer detection through deep learning: An anomaly detection approach using Variational Autoencoder
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Taxonomy-based prompt engineering to generate synthetic drug-related patient portal messages
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Structural analysis and intelligent classification of clinical trial eligibility criteria based on deep learning and medical text mining
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Biomedical document-level relation extraction with thematic capture and localized entity pooling
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How to identify patient perception of AI voice robots in the follow-up scenario? A multimodal identity perception method based on deep learning
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Machine learning approaches for the discovery of clinical pathways from patient data: A systematic review
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Modeling repeated measurements data using the Multilevel Bayesian network: A case of child morbidity
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Enhancing suicidal behavior detection in EHRs: A multi-label NLP framework with transformer models and semantic retrieval-based annotation
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Coherence and comprehensibility: Large language models predict lay understanding of health-related content
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A multimodal approach for few-shot biomedical named entity recognition in low-resource languages
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Novel machine learning model for predicting cancer drugs’ susceptibilities and discovering novel treatments
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Efficient strabismus diagnosis from small samples: Harnessing spatial features for improved accuracy
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Updating and recalibrating causal probabilistic models on a new target population
Updating and recalibrating causal probabilistic models on a new target population
To be clinically useful, a Bayesian Network (BN) needs to function well in different populations. For example, a model sho...
Enhanced Family History-Based Algorithms Increase the Identification of Individuals Meeting Criteria for Genetic Testing of Hereditary Cancer Syndromes but Would Not Reduce Disparities on Their Own
Enhanced Family History-Based Algorithms Increase the Identification of Individuals Meeting Criteria for Genetic Testing of Hereditary Cancer Syndromes but Would Not Reduce Disparities on Their Own
Recent widespread adoption of electronic health records (EHRs) is revolutionizing healthcare. Larger volumes of electronic...
Evaluation of clinical practice guideline-derived clinical decision support systems using a novel quality model
Evaluation of clinical practice guideline-derived clinical decision support systems using a novel quality model
Today, any organization requires innovative, flexible solutions to digitize and automate their processes [2] in conjunctio...
Re-ordered fuzzy conformance checking for uncertain clinical records
Re-ordered fuzzy conformance checking for uncertain clinical records
Clinical pathways have been widely adopted in the past years to standardize patient treatments [1], [2]. A number of clini...
Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance
Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance
Promoting diversity and inclusion is crucial in precision medicine research as many demographic sub-populations are observ...
Obtaining Clinical Term Embeddings from SNOMED CT Ontology
Obtaining Clinical Term Embeddings from SNOMED CT Ontology
Deep learning based methods have shown success on several natural language processing (NLP) tasks, including in the clinic...
Language Inference-based Learning for Low-Resource Chinese Clinical Named Entity Recognition Using Language Model
Language Inference-based Learning for Low-Resource Chinese Clinical Named Entity Recognition Using Language Model
Electronic health records (EHRs) have been broadly employed in China, along with the development of medical informatics. T...
Ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices
Ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices
Introduction:Advances in wearable sensor technology have enabled the collection of biomarkers that may correlate with leve...
Efficient Adversarial debiasing with Concept Activation Vector—Medical image case-studies
Efficient Adversarial debiasing with Concept Activation Vector—Medical image case-studies
Bias and discrimination in Artificial Intelligence (AI) systems has been studied in multiple domains including healthcare ...
Convert-Pheno: A software toolkit for the interconversion of standard data models for phenotypic data
Convert-Pheno: A software toolkit for the interconversion of standard data models for phenotypic data
Structured storage of phenotypic and clinical data (“pheno-clinical”), which encompasses the organized collection of infor...
Fair Patient Model: Mitigating Bias in the Patient Representation Learned from the Electronic Health Records
Fair Patient Model: Mitigating Bias in the Patient Representation Learned from the Electronic Health Records
Electronic Health Records (EHRs) have revolutionized the way patient data is collected and stored in healthcare settings. ...
Towards a Framework for Interoperability and Reproducibility of Predictive Models
Towards a Framework for Interoperability and Reproducibility of Predictive Models
Increased computational power, alongside access to the abundance of electronic health records (EHRs) and other emergent ty...
Data and models for stance and premise detection in COVID-19 tweets: Insights from the Social Media Mining for Health (SMM4H) 2022 shared task
Data and models for stance and premise detection in COVID-19 tweets: Insights from the Social Media Mining for Health (SMM4H) 2022 shared task
In recent years, social media platforms have become powerful channels for public discourse, shaping opinions, and dissemin...
Advancing Italian Biomedical Information Extraction with Transformers-based Models: Methodological Insights and Multicenter Practical Application
Advancing Italian Biomedical Information Extraction with Transformers-based Models: Methodological Insights and Multicenter Practical Application
The ubiquity of digital technologies is increasingly encompassing every aspect of our lives, and healthcare is no exceptio...
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