AIMC Topic: Deep Learning

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A new deep learning framework based on blood pressure range constraint for continuous cuffless BP estimation.

Neural networks : the official journal of the International Neural Network Society
Blood pressure (BP) is known as an indicator of human health status, and regular measurement is helpful for early detection of cardiovascular diseases. Traditional techniques for measuring BP are either invasive or cuff-based and thus are not suitabl...

Study on transfer learning capabilities for pneumonia classification in chest-x-rays images.

Computer methods and programs in biomedicine
BACKGROUND: over the last year, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants have highlighted the importance of screening tools with high diagnostic accuracy for new illnesses such as COVID-19. In that regard, dee...

Machine Learning, Deep Learning, and Mathematical Models to Analyze Forecasting and Epidemiology of COVID-19: A Systematic Literature Review.

International journal of environmental research and public health
COVID-19 is a disease caused by SARS-CoV-2 and has been declared a worldwide pandemic by the World Health Organization due to its rapid spread. Since the first case was identified in Wuhan, China, the battle against this deadly disease started and ha...

Forecasting Multiple Groundwater Time Series with Local and Global Deep Learning Networks.

International journal of environmental research and public health
Time series data from environmental monitoring stations are often analysed with machine learning methods on an individual basis, however recent advances in the machine learning field point to the advantages of incorporating multiple related time seri...

Fully Automated Wound Tissue Segmentation Using Deep Learning on Mobile Devices: Cohort Study.

JMIR mHealth and uHealth
BACKGROUND: Composition of tissue types within a wound is a useful indicator of its healing progression. Tissue composition is clinically used in wound healing tools (eg, Bates-Jensen Wound Assessment Tool) to assess risk and recommend treatment. How...

Understanding the Research Landscape of Deep Learning in Biomedical Science: Scientometric Analysis.

Journal of medical Internet research
BACKGROUND: Advances in biomedical research using deep learning techniques have generated a large volume of related literature. However, there is a lack of scientometric studies that provide a bird's-eye view of them. This absence has led to a partia...

Subjective machines: Probabilistic risk assessment based on deep learning of soft information.

Risk analysis : an official publication of the Society for Risk Analysis
For several years machine learning methods have been proposed for risk classification. While machine learning methods have also been used for failure diagnosis and condition monitoring, to the best of our knowledge, these methods have not been used f...

Histopathology-Based Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning.

Journal of dental research
Oral squamous cell carcinoma (OSCC) is prevalent around the world and is associated with poor prognosis. OSCC is typically diagnosed from tissue biopsy sections by pathologists who rely on their empirical experience. Deep learning models may improve ...

Deep learning-based prediction of molecular cancer biomarkers from tissue slides: A new tool for precision oncology.

Clinical and molecular hepatology
Molecular tests are necessary to stratify cancer patients for targeted therapy. However, high cost and technical barriers limit the application of these tests, hindering optimal treatment. Recently, deep learning (DL) has been applied to predict mole...

Pseudoprospective Paraclinical Interaction of Radiology Residents With a Deep Learning System for Prostate Cancer Detection: Experience, Performance, and Identification of the Need for Intermittent Recalibration.

Investigative radiology
OBJECTIVES: The aim of this study was to estimate the prospective utility of a previously retrospectively validated convolutional neural network (CNN) for prostate cancer (PC) detection on prostate magnetic resonance imaging (MRI).