AIMC Topic: Humans

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ResNet-BiLSTM: A Multiscale Deep Learning Model for Heartbeat Detection Using Ballistocardiogram Signals.

Journal of healthcare engineering
As the heartbeat detection from ballistocardiogram (BCG) signals using force sensors is interfered by respiratory effort and artifact motion, advanced signal processing algorithms are required to detect the J-peak of each BCG signal so that beat-to-b...

A Novel Deep Learning-Based Black Fungus Disease Identification Using Modified Hybrid Learning Methodology.

Contrast media & molecular imaging
Currently, countries across the world are suffering from a prominent viral infection called COVID-19. Most countries are still facing several issues due to this disease, which has resulted in several fatalities. The first COVID-19 wave caused devasta...

Deep neural network models of sound localization reveal how perception is adapted to real-world environments.

Nature human behaviour
Mammals localize sounds using information from their two ears. Localization in real-world conditions is challenging, as echoes provide erroneous information and noises mask parts of target sounds. To better understand real-world localization, we equi...

Breast lesions classifications of mammographic images using a deep convolutional neural network-based approach.

PloS one
Breast cancer is one of the worst illnesses, with a higher fatality rate among women globally. Breast cancer detection needs accurate mammography interpretation and analysis, which is challenging for radiologists owing to the intricate anatomy of the...

Deep learning model calibration for improving performance in class-imbalanced medical image classification tasks.

PloS one
In medical image classification tasks, it is common to find that the number of normal samples far exceeds the number of abnormal samples. In such class-imbalanced situations, reliable training of deep neural networks continues to be a major challenge...

WBC-AMNet: Automatic classification of WBC images using deep feature fusion network based on focalized attention mechanism.

PloS one
The recognition and classification of White Blood Cell (WBC) play a remarkable role in blood-related diseases (i.e., leukemia, infections) diagnosis. For the highly similar morphology of different WBC subtypes, it is too confused to classify the WBC ...

Deep Learning Algorithm for Automated Detection of Polycystic Ovary Syndrome Using Scleral Images.

Frontiers in endocrinology
The high prevalence of polycystic ovary syndrome (PCOS) among reproductive-aged women has attracted more and more attention. As a common disorder that is likely to threaten women's health physically and mentally, the detection of PCOS is a growing pu...

A Deep Learning Approach for MRI in the Diagnosis of Labral Injuries of the Hip Joint.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The diagnosis of labral injury on MRI is time-consuming and potential for incorrect diagnoses.

Evaluation of a deep learning model on coronary CT angiography for automatic stenosis detection.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to evaluate a deep-learning model (DLM) for classifying coronary arteries on coronary computed tomography -angiography (CCTA) using the Coronary Artery Disease-Reporting and Data System (CAD-RADS).