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Leveraging electronic health records for atrial fibrillation cohort generation
Leveraging electronic health records for atrial fibrillation cohort generation
Cohort selection and eligibility screening are critical in clinical research, especially in trials where manual patient ma...
Retrieval augmented large language model system for comprehensive drug contraindications
Retrieval augmented large language model system for comprehensive drug contraindications
The versatility of large language models (LLMs) has been explored across various sectors, but their application in healthc...
Inter-clinician diagnostic agreement of shock etiology: a multicenter observational study
Inter-clinician diagnostic agreement of shock etiology: a multicenter observational study
We sought to (1) quantify lack of inter-clinician diagnostic agreement of shock etiology and (2) predict patients without ...
Protein–protein interaction extraction enhanced by entity semantic representation
Protein–protein interaction extraction enhanced by entity semantic representation
Aiming to address key challenges in biomedical text mining, this paper proposes a protein–protein interaction (PPI) ...
Healthcare utilization and chronic condition clusters in multimorbidity patients using weighted k-means: a register-based study in Denmark
Healthcare utilization and chronic condition clusters in multimorbidity patients using weighted k-means: a register-based study in Denmark
The growing burden of multimorbidity challenges the healthcare system due to increased healthcare utilization and uncoordi...
HeteroMed: a heterogeneous graph knowledge-enhanced model for medication recommendation
HeteroMed: a heterogeneous graph knowledge-enhanced model for medication recommendation
Medication recommendation aims to generate treatment regimens that balance efficacy and safety based on patients’ hi...
Consistent explainable image quality assessment for medical imaging
Consistent explainable image quality assessment for medical imaging
Medical image quality assessment is crucial, as poor-quality images can lead to misdiagnosis. Manual quality labeling is t...
Large language models and conditional rules in clinical decision support systems
Large language models and conditional rules in clinical decision support systems
Clinical Decision Support Systems (CDSS) improve patient outcomes and support sustainable health services by enhancing med...
Machine learning models for volume and weight estimation in breast reconstruction planning
Machine learning models for volume and weight estimation in breast reconstruction planning
Accurate estimation of breast volume and weight is critical for post-mastectomy reconstruction. Existing methods are frequ...
Optimizing ED patient disposition predictions through clinical narratives with advanced pre-trained language models
Optimizing ED patient disposition predictions through clinical narratives with advanced pre-trained language models
Timely identification of febrile patients requiring hospitalization remains a significant challenge in Emergency Departmen...
Exploring the potential of large language models in healthcare: a focus on cardiovascular disease analysis
Exploring the potential of large language models in healthcare: a focus on cardiovascular disease analysis
With the rapid development of big data and artificial intelligence technologies, large language models (LLMs) are increasi...
Pose2met: a unified spatiotemporal framework for 3D human pose estimation and energy expenditure estimation
Pose2met: a unified spatiotemporal framework for 3D human pose estimation and energy expenditure estimation
This study addresses key challenges in 3D human pose estimation (HPE) and energy expenditure estimation (EEE), focusing on...
A data fusion deep learning approach for accurate organelle-based classification of cancer cells
A data fusion deep learning approach for accurate organelle-based classification of cancer cells
Microscopy-based cancer cell classification traditionally relies on cell-based morphological features, while subcellular o...
Big data in healthcare and medicine revisited design and managerial challenges in the age of artificial intelligence
Big data in healthcare and medicine revisited design and managerial challenges in the age of artificial intelligence
A decade ago, we characterized big data in healthcare as a nascent field anchored in distributed computing paradigms. The ...
ACDW-InceptionNeXt: adjacent class distinguished and class distance weighted InceptionNeXt-based computer-aided mayo endoscopic scoring system for still images and video segments
ACDW-InceptionNeXt: adjacent class distinguished and class distance weighted InceptionNeXt-based computer-aided mayo endoscopic scoring system for still images and video segments
Ulcerative colitis (UC) is commonly assessed using the Mayo endoscopic subscore (MES), which classifies disease severity i...
MedGAITS: a graph autoencoder network for modeling irregular time series data in electronic medical records
MedGAITS: a graph autoencoder network for modeling irregular time series data in electronic medical records
The widespread adoption of electronic medical records (EMR) has facilitated the prediction of patient prognosis and diseas...
Complex temporal network analysis based on the difference visibility graph for epilepsy with and without electrical status epilepticus during sleep (ESES) patients
Complex temporal network analysis based on the difference visibility graph for epilepsy with and without electrical status epilepticus during sleep (ESES) patients
Epilepsy with electrical status epilepticus during sleep (ESES) is a distinct form of epileptic encephalopathy in childhoo...
LDComKG: an LLM-powered dual-enhanced framework for community-aware knowledge graph completion in traditional Chinese medicine
LDComKG: an LLM-powered dual-enhanced framework for community-aware knowledge graph completion in traditional Chinese medicine
The intricate semantics, diverse terminology, and lack of standardization in ancient Chinese medical corpora present formi...
An enhanced heart disease prediction model based on linear Diophantine fuzzy-integrated supervised machine learning
An enhanced heart disease prediction model based on linear Diophantine fuzzy-integrated supervised machine learning
The medical diagnosis often dealt with uncertainty and vagueness that hindered the effectiveness of conventional ML approa...
An augmented ECG data based classification for arrhythmia using optimal feature set
An augmented ECG data based classification for arrhythmia using optimal feature set
The Electrocardiogram (ECG) is a pivotal tool for diagnosing heart conditions such as arrhythmia. Prompt detection of arrh...
Leveraging patients’ longitudinal data to improve the Hospital One-year Mortality Risk
Leveraging patients’ longitudinal data to improve the Hospital One-year Mortality Risk
Predicting medium-term survival after admission is necessary for identifying end-of-life patients who may benefit from goa...
iAMP-CRA: Identifying Antimicrobial Peptides Using Convolutional Recurrent Neural Network with Self-Attention
iAMP-CRA: Identifying Antimicrobial Peptides Using Convolutional Recurrent Neural Network with Self-Attention
Antimicrobial peptides (AMPs) are natural polypeptides with antibacterial activity and are an important part of the innate...
Towards cognition–emotion–behaviour models of nonsuicidal self-injury: a knowledge graph approach
Towards cognition–emotion–behaviour models of nonsuicidal self-injury: a knowledge graph approach
Non-suicidal self-injury (NSSI) refers to intentionally harming one’s own body tissue without intending to die or ca...
Hyperbolic vision language representation learning on chest radiology images
Hyperbolic vision language representation learning on chest radiology images
Given the visual-semantic hierarchy between images and texts, hyperbolic embeddings have been employed for visual-semantic...
CSL-CTEA: a systematic method for evaluating novel intelligent cognitive assessment tools
CSL-CTEA: a systematic method for evaluating novel intelligent cognitive assessment tools
With the intensification of global population aging, the incidence of cognitive disorders such as dementia continues to ri...
Leveraging deep learning for epigenetic protein prediction: a novel approach for early lung cancer diagnosis and drug discovery
Leveraging deep learning for epigenetic protein prediction: a novel approach for early lung cancer diagnosis and drug discovery
Epigenetic protein (EP) plays a crucial role in influencing disease development, controlling gene expression, and shaping ...
Optimized seizure detection leveraging band-specific insights from limited EEG channels
Optimized seizure detection leveraging band-specific insights from limited EEG channels
Effective seizure detection systems are crucial for health information systems and managing epilepsy, yet traditional mult...
GEP-DNN4Mol: automatic chemical molecular design based on deep neural networks and gene expression programming
GEP-DNN4Mol: automatic chemical molecular design based on deep neural networks and gene expression programming
The inverse design of molecules has attracted widespread attention in the field of chemical molecular design. However, exi...
Spatial and frequency domain-based feature fusion for accurate detection of schizophrenia using AI-driven approaches
Spatial and frequency domain-based feature fusion for accurate detection of schizophrenia using AI-driven approaches
Schizophrenia is a neuropsychiatric disorder that hampers brain functions and causes hallucinations, delusions, and bizarr...
Enhancing cancer subtype classification through convolutional neural networks: a deepinsight analysis of TCGA gene expression data
Enhancing cancer subtype classification through convolutional neural networks: a deepinsight analysis of TCGA gene expression data
This study investigates the adaptation of DeepInsight for cancer subtype classification using high-dimensional gene expres...
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