AIMC Topic: Female

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Breast pectoral muscle segmentation in mammograms using a modified holistically-nested edge detection network.

Medical image analysis
This paper presents a method for automatic breast pectoral muscle segmentation in mediolateral oblique mammograms using a Convolutional Neural Network (CNN) inspired by the Holistically-nested Edge Detection (HED) network. Most of the existing method...

Deep-learning-based imaging-classification identified cingulate island sign in dementia with Lewy bodies.

Scientific reports
The differentiation of dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) using brain perfusion single photon emission tomography is important but is challenging because these conditions exhibit typical features. The cingulate island sign ...

Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models.

Breast cancer research : BCR
BACKGROUND: Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminat...

Automatic identification of atherosclerosis subjects in a heterogeneous MR brain imaging data set.

Magnetic resonance imaging
Carotid-artery atherosclerosis (CA) contributes significantly to overall morbidity and mortality in ischemic stroke. We propose a machine learning technique to automatically identify subjects with CA from a heterogeneous cohort of magnetic resonance ...

An automatic single-channel EEG-based sleep stage scoring method based on hidden Markov Model.

Journal of neuroscience methods
OBJECTIVE: Sleep stage scoring is essential for diagnosing sleep disorders. Visual scoring of sleep stages is very time-consuming and prone to human errors. In this work, we introduce an efficient approach to improve the accuracy of sleep stage scori...

An artificial neural network for the prediction of assisted reproduction outcome.

Journal of assisted reproduction and genetics
PURPOSE: To construct and validate an efficient artificial neural network (ANN) based on parameters with statistical correlation to live birth, to be used as a comprehensive tool for the prediction of the clinical outcome for patients undergoing ART.

Diagnosis of Alzheimer's disease with Sobolev gradient-based optimization and 3D convolutional neural network.

International journal for numerical methods in biomedical engineering
Alzheimer's disease is a neuropsychiatric, progressive, also an irreversible disease. There is not an effective cure for the disease. However, early diagnosis has an important role for treatment planning to delay its progression since the treatments ...

Presurgical differentiation between malignant haemangiopericytoma and angiomatous meningioma by a radiomics approach based on texture analysis.

Journal of neuroradiology = Journal de neuroradiologie
PURPOSE: To assess whether a machine-learning model based on texture analysis (TA) could yield a more accurate diagnosis in differentiating malignant haemangiopericytoma (HPC) from angiomatous meningioma (AM).

Diagnostic value of spirometry vs impulse oscillometry: A comparative study in children with sickle cell disease.

Pediatric pulmonology
BACKGROUND: Spirometry is conventionally used to diagnose airway diseases in children with sickle cell disease (C-SCD). However, spirometry is difficult for younger children to perform, is effort dependent, and it provides limited information on resp...