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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...
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 ...
Rapid detection and interpretation of heart murmurs using phonocardiograms, transfer learning and explainable artificial intelligence
Rapid detection and interpretation of heart murmurs using phonocardiograms, transfer learning and explainable artificial intelligence
Cardiovascular disease, which remains one of the main causes of death, can be prevented by early diagnosis of heart sounds...
Convolutional neural network framework for EEG-based ADHD diagnosis in children
Convolutional neural network framework for EEG-based ADHD diagnosis in children
Attention-deficit hyperactivity disorder (ADHD) stands as a significant psychiatric and neuro-developmental disorder with ...
Tree hole rescue: an AI approach for suicide risk detection and online suicide intervention
Tree hole rescue: an AI approach for suicide risk detection and online suicide intervention
Adolescent suicide has become an important social issue of general concern. Many young people express their suicidal feeli...
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...
Jointly constrained group sparse connectivity representation improves early diagnosis of Alzheimer’s disease on routinely acquired T1-weighted imaging-based brain network
Jointly constrained group sparse connectivity representation improves early diagnosis of Alzheimer’s disease on routinely acquired T1-weighted imaging-based brain network
Radiomics-based morphological brain networks (radMBN) constructed from routinely acquired structural MRI (sMRI) data have ...
Efficient management of pulmonary embolism diagnosis using a two-step interconnected machine learning model based on electronic health records data
Efficient management of pulmonary embolism diagnosis using a two-step interconnected machine learning model based on electronic health records data
Pulmonary Embolism (PE) is a life-threatening clinical disease with no specific clinical symptoms and Computed Tomography ...
Identification of cancer driver genes based on hierarchical weak consensus model
Identification of cancer driver genes based on hierarchical weak consensus model
Cancer is a complex gene mutation disease that derives from the accumulation of mutations during somatic cell evolution. W...
Enhancing ASD detection accuracy: a combined approach of machine learning and deep learning models with natural language processing
Enhancing ASD detection accuracy: a combined approach of machine learning and deep learning models with natural language processing
The main aim of our study was to explore the utility of artificial intelligence (AI) in diagnosing autism spectrum disorde...
Optimised deep k-nearest neighbour’s based diabetic retinopathy diagnosis(ODeep-NN) using retinal images
Optimised deep k-nearest neighbour’s based diabetic retinopathy diagnosis(ODeep-NN) using retinal images
Diabetes mellitus has been regarded as one of the prime health issues in present days, which can often lead to diabetic re...
Artificial intelligence-based framework to identify the abnormalities in the COVID-19 disease and other common respiratory diseases from digital stethoscope data using deep CNN
Artificial intelligence-based framework to identify the abnormalities in the COVID-19 disease and other common respiratory diseases from digital stethoscope data using deep CNN
The utilization of lung sounds to diagnose lung diseases using respiratory sound features has significantly increased in t...
Gpmb-yolo: a lightweight model for efficient blood cell detection in medical imaging
Gpmb-yolo: a lightweight model for efficient blood cell detection in medical imaging
In the field of biomedical science, blood cell detection in microscopic images is crucial for aiding physicians in diagnos...
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...
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