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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 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...
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 ...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
Analyzing and identifying predictable time range for stress prediction based on chaos theory and deep learning
Analyzing and identifying predictable time range for stress prediction based on chaos theory and deep learning
Stress is a common problem globally. Prediction of stress in advance could help people take effective measures to manage s...
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 ...
Autism spectrum disorder detection with kNN imputer and machine learning classifiers via questionnaire mode of screening
Autism spectrum disorder detection with kNN imputer and machine learning classifiers via questionnaire mode of screening
Autism spectrum disorder (ASD) is a neurodevelopmental disorder. ASD cannot be fully cured, but early-stage diagnosis foll...
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 ...
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...
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...
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...
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...
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