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Creating a computer assisted ICD coding system: Performance metric choice and use of the ICD hierarchy
Creating a computer assisted ICD coding system: Performance metric choice and use of the ICD hierarchy
Objective:Machine learning methods hold the promise of leveraging available data and generating higher-quality data while ...
Improving the interoperability of drugs terminologies: Infusing local standardization with an international perspective
Improving the interoperability of drugs terminologies: Infusing local standardization with an international perspective
Volume 151, March 2024, 104614Author links open overlay panel, , , , AbstractObjectives:The objective of this study is to ...
Multi-view representation learning for tabular data integration using inter-feature relationships
Multi-view representation learning for tabular data integration using inter-feature relationships
Objective:An applied problem facing all areas of data science is harmonizing data sources. Joining data from multiple orig...
Evaluating the dynamic interplay of social distancing policies regarding airborne pathogens through a temporal interaction-driven model that uses real-world and synthetic data
Evaluating the dynamic interplay of social distancing policies regarding airborne pathogens through a temporal interaction-driven model that uses real-world and synthetic data
The SARS-CoV-2 coronavirus disease 2019 (COVID-19) has created a global crisis. In response, governments and local authori...
Temporal attention networks for biomedical hypothesis generation
Temporal attention networks for biomedical hypothesis generation
A large body of publicly accessible literature has become the driving force for research innovation. New, meaningful impli...
SPeC: A Soft Prompt-Based Calibration on Performance Variability of Large Language Model in Clinical Notes Summarization
SPeC: A Soft Prompt-Based Calibration on Performance Variability of Large Language Model in Clinical Notes Summarization
Electronic health records (EHRs) have brought about a revolutionary change in the accessibility and utilization of patient...
Detecting goals of care conversations in clinical notes with active learning
Detecting goals of care conversations in clinical notes with active learning
Volume 151, March 2024, 104618Author links open overlay panel, , , , , , , , , , Highlights•We manually annotated Goals-of...
Extracting adverse drug events from clinical Notes: A systematic review of approaches used
Extracting adverse drug events from clinical Notes: A systematic review of approaches used
Adverse drug events (ADEs), according to the World Health Organization (WHO), are defined as any injury or unfavorable con...
Data integration through canonical correlation analysis and its application to OMICs research
Data integration through canonical correlation analysis and its application to OMICs research
Modern molecular measuring technologies i.e. Next Generation Sequencing (NGS) and other ultra-high throughput experimental...
Graph neural networks for clinical risk prediction based on electronic health records: A survey
Graph neural networks for clinical risk prediction based on electronic health records: A survey
AbbreviationsEHRElectronic health recordGCNGraph convolutional networkGATGraph attention networkCNNConvolutional neural ne...
Evaluation of ChatGPT-generated medical responses: A systematic review and meta-analysis
Evaluation of ChatGPT-generated medical responses: A systematic review and meta-analysis
In recent years, large language models (LLMs) have attracted attention for their potential to improve traditional approach...
A scoping review of fair machine learning techniques when using real-world data
A scoping review of fair machine learning techniques when using real-world data
Volume 151, March 2024, 104622Author links open overlay panel, , , , , , , AbstractObjectiveThe integration of artificial ...
Artificial intelligence-powered pharmacovigilance: A review of machine and deep learning in clinical text-based adverse drug event detection for benchmark datasets
Artificial intelligence-powered pharmacovigilance: A review of machine and deep learning in clinical text-based adverse drug event detection for benchmark datasets
Adverse Drug Event (ADE) refers to harm caused by medical interventions associated with drugs, involving overdoses, allerg...
ParTRE: A relational triple extraction model of complicated entities and imbalanced relations in Parkinson’s disease
ParTRE: A relational triple extraction model of complicated entities and imbalanced relations in Parkinson’s disease
Parkinson’s disease (PD), characterized by static tremors and slow movements, is the world’s second most common progressiv...
A comprehensive performance evaluation, comparison, and integration of computational methods for detecting and estimating cross-contamination of human samples in cancer next-generation sequencing analysis
A comprehensive performance evaluation, comparison, and integration of computational methods for detecting and estimating cross-contamination of human samples in cancer next-generation sequencing analysis
Next-generation sequencing (NGS) has been widely used in diagnostic molecular biology laboratories to identify pathogenic ...
Soft phenotyping for sepsis via EHR time-aware soft clustering
Soft phenotyping for sepsis via EHR time-aware soft clustering
Sepsis is a life-threatening organ dysfunction syndrome secondary to a dysregulated host response to infection, and the pr...
FedFSA: Hybrid and federated framework for functional status ascertainment across institutions
FedFSA: Hybrid and federated framework for functional status ascertainment across institutions
Patients' functional status assesses their independence in performing activities of daily living (ADL), including basic AD...
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...
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