AI Medical Compendium Topic

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The Feature Ambiguity Mitigate Operator model helps improve bone fracture detection on X-ray radiograph.

Scientific reports
This study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, to mitigate feature ambiguity in bone fracture detection on radiographs of various body parts. A total of 9040 radiographic studies were extracted. Th...

Supervised machine learning for automated classification of human Wharton's Jelly cells and mechanosensory hair cells.

PloS one
Tissue engineering and gene therapy strategies offer new ways to repair permanent damage to mechanosensory hair cells (MHCs) by differentiating human Wharton's Jelly cells (HWJCs). Conventionally, these strategies require the classification of each c...

Deep learning applied to two-dimensional color Doppler flow imaging ultrasound images significantly improves diagnostic performance in the classification of breast masses: a multicenter study.

Chinese medical journal
BACKGROUND: The current deep learning diagnosis of breast masses is mainly reflected by the diagnosis of benign and malignant lesions. In China, breast masses are divided into four categories according to the treatment method: inflammatory masses, ad...

Convolutional Neural Networks for Pediatric Refractory Epilepsy Classification Using Resting-State Functional Magnetic Resonance Imaging.

World neurosurgery
OBJECTIVE: This study aims to evaluate the performance of convolutional neural networks (CNNs) trained with resting-state functional magnetic resonance imaging (rfMRI) latency data in the classification of patients with pediatric epilepsy from health...

Prediction of implementing ISO 14031 guidelines using a multilayer perceptron neural network approach.

PloS one
The purpose of this study was to model the link between the implementation of ISO 14031 and ISO 14001. This study connects ISO 14031's guidelines as independent variables to a dependent variable expressed by the ISO 14001 certification situation of i...

Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study.

PloS one
BACKGROUND: A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making rega...

Development and evaluation of deep learning for screening dental caries from oral photographs.

Oral diseases
OBJECTIVES: To develop and evaluate the performance of a deep learning system based on convolutional neural network (ConvNet) to detect dental caries from oral photographs.

Prediction of disease progression in patients with COVID-19 by artificial intelligence assisted lesion quantification.

Scientific reports
To investigate the value of artificial intelligence (AI) assisted quantification on initial chest CT for prediction of disease progression and clinical outcome in patients with coronavirus disease 2019 (COVID-19). Patients with confirmed COVID-19 inf...

Graph embeddings on gene ontology annotations for protein-protein interaction prediction.

BMC bioinformatics
BACKGROUND: Protein-protein interaction (PPI) prediction is an important task towards the understanding of many bioinformatics functions and applications, such as predicting protein functions, gene-disease associations and disease-drug associations. ...