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Linguistic summarization of visual attention and developmental functioning of young children with autism spectrum disorder
Linguistic summarization of visual attention and developmental functioning of young children with autism spectrum disorder
Diagnosing autism spectrum disorder (ASD) in children poses significant challenges due to its complex nature and impact on...
A novel multi-modal model to assist the diagnosis of autism spectrum disorder using eye-tracking data
A novel multi-modal model to assist the diagnosis of autism spectrum disorder using eye-tracking data
Timely and accurate detection of Autism Spectrum Disorder (ASD) is essential for early intervention and improved patient o...
Comprehensive applications of the artificial intelligence technology in new drug research and development
Comprehensive applications of the artificial intelligence technology in new drug research and development
Target-based strategy is a prevalent means of drug research and development (R&D), since targets provide effector ...
Optimized automated detection of diabetic retinopathy severity: integrating improved multithresholding tunicate swarm algorithm and improved hybrid butterfly optimization
Optimized automated detection of diabetic retinopathy severity: integrating improved multithresholding tunicate swarm algorithm and improved hybrid butterfly optimization
Diabetic retinopathy, a complication of diabetes, damages the retina due to prolonged high blood sugar levels, leading to ...
A lightweight network based on multi-feature pseudo-color mapping for arrhythmia recognition
A lightweight network based on multi-feature pseudo-color mapping for arrhythmia recognition
Heartbeats classification is a crucial tool for arrhythmia diagnosis. In this study, a multi-feature pseudo-color mapping ...
Explainable depression symptom detection in social media
Explainable depression symptom detection in social media
Users of social platforms often perceive these sites as supportive spaces to post about their mental health issues. Those ...
Comorbidity progression analysis: patient stratification and comorbidity prediction using temporal comorbidity network
Comorbidity progression analysis: patient stratification and comorbidity prediction using temporal comorbidity network
The study aims to identify distinct population-specific comorbidity progression patterns, timely detect potential comorbid...
Explainable federated learning scheme for secure healthcare data sharing
Explainable federated learning scheme for secure healthcare data sharing
Artificial intelligence has immense potential for applications in smart healthcare. Nowadays, a large amount of medical da...
Machine learning approach to flare-up detection and clustering in chronic obstructive pulmonary disease (COPD) patients
Machine learning approach to flare-up detection and clustering in chronic obstructive pulmonary disease (COPD) patients
Chronic obstructive pulmonary disease (COPD) is a prevalent and preventable condition that typically worsens over time. Ac...
Dynamically stabilized recurrent neural network optimized with Artificial Gorilla Troops espoused Alzheimer’s disorder detection using EEG signals
Dynamically stabilized recurrent neural network optimized with Artificial Gorilla Troops espoused Alzheimer’s disorder detection using EEG signals
Alzheimer’s disease is an incurable neurological disorder that damages cognitive abilities, but early identification...
Alterations of DNA methylation profile in peripheral blood of children with simple obesity
Alterations of DNA methylation profile in peripheral blood of children with simple obesity
To investigate the association between DNA methylation and childhood simple obesity. Genome-wide analysis of DNA methylati...
A drug prescription recommendation system based on novel DIAKID ontology and extensive semantic rules
A drug prescription recommendation system based on novel DIAKID ontology and extensive semantic rules
According to the World Health Organization (WHO) data from 2000 to 2019, the number of people living with Diabetes Mellitu...
Image-based second opinion for blood typing
Image-based second opinion for blood typing
This paper considers a new method for providing a recommendation (second opinion) for a laboratory assistant in manual blo...
Characterization of biliary and duodenal microbiota in patients with primary and recurrent choledocholithiasis
Characterization of biliary and duodenal microbiota in patients with primary and recurrent choledocholithiasis
To explore the biliary and duodenal microbiota features associated with the formation and recurrence of choledocholithiasi...
A review of machine learning-based methods for predicting drug–target interactions
A review of machine learning-based methods for predicting drug–target interactions
The prediction of drug–target interactions (DTI) is a crucial preliminary stage in drug discovery and development, g...
Exploiting biochemical data to improve osteosarcoma diagnosis with deep learning
Exploiting biochemical data to improve osteosarcoma diagnosis with deep learning
Early and accurate diagnosis of osteosarcomas (OS) is of great clinical significance, and machine learning (ML) based meth...
Spatial-attention ConvMixer architecture for classification and detection of gastrointestinal diseases using the Kvasir dataset
Spatial-attention ConvMixer architecture for classification and detection of gastrointestinal diseases using the Kvasir dataset
Gastrointestinal (GI) disorders, encompassing conditions like cancer and Crohn’s disease, pose a significant threat ...
A hybrid approach based on multipath Swin transformer and ConvMixer for white blood cells classification
A hybrid approach based on multipath Swin transformer and ConvMixer for white blood cells classification
White blood cells (WBC) play an effective role in the body’s defense against parasites, viruses, and bacteria in the...
Development of a recommendation system and data analysis in personalized medicine: an approach towards healthy vascular ageing
Development of a recommendation system and data analysis in personalized medicine: an approach towards healthy vascular ageing
Understanding early vascular ageing has become crucial for preventing adverse cardiovascular events. To this respect, rece...
Harbor seal whiskers optimization algorithm with deep learning-based medical imaging analysis for gastrointestinal cancer detection
Harbor seal whiskers optimization algorithm with deep learning-based medical imaging analysis for gastrointestinal cancer detection
Gastrointestinal (GI) cancer detection includes the detection of cancerous or potentially cancerous lesions within the GI ...
A transfer learning enabled approach for ocular disease detection and classification
A transfer learning enabled approach for ocular disease detection and classification
Ocular diseases pose significant challenges in timely diagnosis and effective treatment. Deep learning has emerged as a pr...
A multi-source heterogeneous medical data enhancement framework based on lakehouse
A multi-source heterogeneous medical data enhancement framework based on lakehouse
Obtaining high-quality data sets from raw data is a key step before data exploration and analysis. Nowadays, in the medica...
Improving laryngeal cancer detection using chaotic metaheuristics integration with squeeze-and-excitation resnet model
Improving laryngeal cancer detection using chaotic metaheuristics integration with squeeze-and-excitation resnet model
Laryngeal cancer (LC) represents a substantial world health problem, with diminished survival rates attributed to late-sta...
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...
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