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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...
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...
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...
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...
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...
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 ...
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...
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...
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...
Self-supervised neural network-based endoscopic monocular 3D reconstruction method
Self-supervised neural network-based endoscopic monocular 3D reconstruction method
Based on deep learning, monocular visual 3D reconstruction methods have been applied in various conventional fields. In th...
LCRNet: local cross-channel recalibration network for liver cancer classification based on CT images
LCRNet: local cross-channel recalibration network for liver cancer classification based on CT images
Liver cancer is the leading cause of mortality in the world. Over the years, researchers have spent much effort in develop...
Deep-kidney: an effective deep learning framework for chronic kidney disease prediction
Deep-kidney: an effective deep learning framework for chronic kidney disease prediction
Chronic kidney disease (CKD) is one of today’s most serious illnesses. Because this disease usually does not manifes...
Viewpoint-invariant exercise repetition counting
Viewpoint-invariant exercise repetition counting
Counting the repetition of human exercise and physical rehabilitation is common in rehabilitation and exercise training. T...
Cardiac murmur grading and risk analysis of cardiac diseases based on adaptable heterogeneous-modality multi-task learning
Cardiac murmur grading and risk analysis of cardiac diseases based on adaptable heterogeneous-modality multi-task learning
Cardiovascular disease (CVDs) has become one of the leading causes of death, posing a significant threat to human life. Th...
CLAD-Net: cross-layer aggregation attention network for real-time endoscopic instrument detection
CLAD-Net: cross-layer aggregation attention network for real-time endoscopic instrument detection
As medical treatments continue to advance rapidly, minimally invasive surgery (MIS) has found extensive applications acros...
Automated lead toxicity prediction using computational modelling framework
Automated lead toxicity prediction using computational modelling framework
Lead, an environmental toxicant, accounts for 0.6% of the global burden of disease, with the highest burden in developing&...