AIMC Topic: Sensitivity and Specificity

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Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning.

Scientific reports
Oral Squamous Cell Carcinoma (OSCC) is a common type of cancer of the oral epithelium. Despite their high impact on mortality, sufficient screening methods for early diagnosis of OSCC often lack accuracy and thus OSCCs are mostly diagnosed at a late ...

Validation of a Machine Learning Approach for Venous Thromboembolism Risk Prediction in Oncology.

Disease markers
Using kernel machine learning (ML) and random optimization (RO) techniques, we recently developed a set of venous thromboembolism (VTE) risk predictors, which could be useful to devise a web interface for VTE risk stratification in chemotherapy-treat...

Depression recognition according to heart rate variability using Bayesian Networks.

Journal of psychiatric research
BACKGROUND: Doctors mainly use scale tests and subjective judgment in the clinical diagnosis of depression. Researches have demonstrated that depression is associated with the dysfunction of the autonomic nervous system (ANS), where its modulation ca...

Multi-label Inductive Matrix Completion for Joint MGMT and IDH1 Status Prediction for Glioma Patients.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
MGMT promoter methylation and IDH1 mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with better prognosis. Traditionally, the statuses of MGMT and IDH1 are obtained via surgical biopsy, which is...

Deformable Image Registration based on Similarity-Steered CNN Regression.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Existing deformable registration methods require exhaustively iterative optimization, along with careful parameter tuning, to estimate the deformation field between images. Although some learning-based methods have been proposed for initiating deform...

An artificial neural network to predict resting energy expenditure in obesity.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND & AIMS: The resting energy expenditure (REE) determination is important in nutrition for adequate dietary prescription. The gold standard i.e. indirect calorimetry is not available in clinical settings. Thus, several predictive equations h...

Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment.

Scientific reports
Rhegmatogenous retinal detachment (RRD) is a serious condition that can lead to blindness; however, it is highly treatable with timely and appropriate treatment. Thus, early diagnosis and treatment of RRD is crucial. In this study, we applied deep le...

Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.

Journal of healthcare engineering
Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect the lung cancer in the early stages. In many cases, the diagnosis of identifying the lung cancer depe...

An Alzheimers disease related genes identification method based on multiple classifier integration.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alzheimers disease (AD) is a fatal neurodegenerative disease and the onset of AD is insidious. Full understanding of the AD-related genes (ADGs) has not been completed. The National Center for Biotechnology Information (NCBI...

Non-proliferative diabetic retinopathy symptoms detection and classification using neural network.

Journal of medical engineering & technology
Diabetic retinopathy (DR) causes blindness in the working age for people with diabetes in most countries. The increasing number of people with diabetes worldwide suggests that DR will continue to be major contributors to vision loss. Early detection ...