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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...
A novel clustered-based binary grey wolf optimizer to solve the feature selection problem for uncovering the genetic links between non-Hodgkin lymphomas and rheumatologic diseases
A novel clustered-based binary grey wolf optimizer to solve the feature selection problem for uncovering the genetic links between non-Hodgkin lymphomas and rheumatologic diseases
The growing incidence of Non-Hodgkin lymphomas (NHL) in recent times has brought attention to the need for thorough invest...
Multimodal interpretable data-driven models for early prediction of multidrug resistance using multivariate time series
Multimodal interpretable data-driven models for early prediction of multidrug resistance using multivariate time series
Electronic Health Records (EHRs) serve as a comprehensive repository of multimodal patient health data, combining static d...
Cerebral ischemia detection using deep learning techniques
Cerebral ischemia detection using deep learning techniques
Cerebrovascular accident (CVA), commonly known as stroke, stands as a significant contributor to contemporary mortality an...
Automatic detection of gastrointestinal system abnormalities using deep learning-based segmentation and classification methods
Automatic detection of gastrointestinal system abnormalities using deep learning-based segmentation and classification methods
Early diagnosis and precise treatment of gastrointestinal (GI) diseases are crucial for reducing mortality and improving q...
A high-precision hierarchical registration approach for stain- and scanner-independent colocalization on whole slide images in histopathology
A high-precision hierarchical registration approach for stain- and scanner-independent colocalization on whole slide images in histopathology
The paper presents a high-precision hierarchical registration method to accurately align image coordinates across Whole Sl...
Multi-teacher based knowledge distillation for retinal vessel segmentation
Multi-teacher based knowledge distillation for retinal vessel segmentation
Accurate segmentation of retinal vessels is crucial for the early diagnosis and management of various ocular diseases. Exi...
CnnBoost: a multilevel explainable stacked ensemble framework for effective detection of Myocardial Infarction from 12-lead ECG images using a transformational approach
CnnBoost: a multilevel explainable stacked ensemble framework for effective detection of Myocardial Infarction from 12-lead ECG images using a transformational approach
Electrocardiogram (ECG) is the most commonly used non-invasive diagnostic tool for cardiovascular diseases. However, its i...
JuryFusionNet: a Condorcet’s jury theorem-based CNN ensemble for enhanced monkeypox detection from skin lesion images
JuryFusionNet: a Condorcet’s jury theorem-based CNN ensemble for enhanced monkeypox detection from skin lesion images
Accurate and timely diagnosis of monkeypox (Mpox) is vital for outbreak control and effective treatment. However, its skin...
The role of mitochondria-related proteins in inflammation and autoimmune diseases: a causal analysis using Mendelian randomization and colocalization
The role of mitochondria-related proteins in inflammation and autoimmune diseases: a causal analysis using Mendelian randomization and colocalization
Mitochondria are central to immune regulation, inflammation, and cellular metabolism. Growing evidence suggests that mitoc...
UniMRE: a unified framework for zero-shot medicial relation extraction with large language models
UniMRE: a unified framework for zero-shot medicial relation extraction with large language models
Medical relation extraction aims to extract pairs of entities and their corresponding relations from unstructured text, wh...
From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine
From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine
Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous de...
Identification method of thyroid nodule ultrasonography based on self-supervised learning dual-branch attention learning framework
Identification method of thyroid nodule ultrasonography based on self-supervised learning dual-branch attention learning framework
Thyroid ultrasound is a widely used diagnostic technique for thyroid nodules in clinical practice. However, due to the cha...
MEAs-Filter: a novel filter framework utilizing evolutionary algorithms for cardiovascular diseases diagnosis
MEAs-Filter: a novel filter framework utilizing evolutionary algorithms for cardiovascular diseases diagnosis
Cardiovascular disease management often involves adjusting medication dosage based on changes in electrocardiogram (ECG) s...
A computational model to analyze the impact of birth weight-nutritional status pair on disease development and disease recovery
A computational model to analyze the impact of birth weight-nutritional status pair on disease development and disease recovery
The purpose of this work is to analyse the combined impacts of birth weight and nutritional status on development and reco...
Enhanced performance of EEG-based brain–computer interfaces by joint sample and feature importance assessment
Enhanced performance of EEG-based brain–computer interfaces by joint sample and feature importance assessment
Electroencephalograph (EEG) has been a reliable data source for building brain–computer interface (BCI) systems; how...
Supervised graph contrastive learning for cancer subtype identification through multi-omics data integration
Supervised graph contrastive learning for cancer subtype identification through multi-omics data integration
Cancer is one of the most deadly diseases in the world. Accurate cancer subtype classification is critical for patient dia...
Adaptive filter of frequency bands based coordinate attention network for EEG-based motor imagery classification
Adaptive filter of frequency bands based coordinate attention network for EEG-based motor imagery classification
In the brain-computer interface (BCI), motor imagery (MI) could be defined as the Electroencephalogram (EEG) signals throu...
Hierarchical classification of early microscopic lung nodule based on cascade network
Hierarchical classification of early microscopic lung nodule based on cascade network
Early-stage lung cancer is typically characterized clinically by the presence of isolated lung nodules. Thousands of cases...
Investigating the overlap of machine learning algorithms in the final results of RNA-seq analysis on gene expression estimation
Investigating the overlap of machine learning algorithms in the final results of RNA-seq analysis on gene expression estimation
Advances in computer science in combination with the next-generation sequencing have introduced a new era in biology, enab...
Mdpg: a novel multi-disease diagnosis prediction method based on patient knowledge graphs
Mdpg: a novel multi-disease diagnosis prediction method based on patient knowledge graphs
Diagnosis prediction, a key factor in enhancing healthcare efficiency, remains a focal point in clinical decision support ...
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