AIMC Topic: Deep Learning

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High-Speed On-Site Deep Learning-Based FFR-CT Algorithm: Evaluation Using Invasive Angiography as the Reference Standard.

AJR. American journal of roentgenology
Estimation of fractional flow reserve from coronary CTA (FFR-CT) is an established method of assessing the hemodynamic significance of coronary lesions. However, clinical implementation has progressed slowly, partly because of off-site data transfer...

Deep Learning-Based Estimation of Implantable Collamer Lens Vault Using Optical Coherence Tomography.

American journal of ophthalmology
PURPOSE: To develop and validate a deep learning neural network for automated measurement of implantable collamer lens (ICL) vault using anterior segment optical coherence tomography (AS-OCT).

A comparative study of deep learning-based knowledge-based planning methods for 3D dose distribution prediction of head and neck.

Journal of applied clinical medical physics
PURPOSE: In this paper, we compare four novel knowledge-based planning (KBP) algorithms using deep learning to predict three-dimensional (3D) dose distributions of head and neck plans using the same patients' dataset and quantitative assessment metri...

A deep learning model for predicting optimal distance range in crosslinking mass spectrometry data.

Proteomics
Macromolecular assemblies play an important role in all cellular processes. While there has recently been significant progress in protein structure prediction based on deep learning, large protein complexes cannot be predicted with these approaches. ...

Application of deep learning algorithm in the recognition of cryptococcosis and talaromycosis skin lesions.

Mycoses
BACKGROUND: Cryptococcosis and talaromycosis are known as 'neglected epidemics' due to their high case fatality rates and low concern. Clinically, the skin lesions of the two fungal diseases are similar and easily misdiagnosed. Therefore, this study ...

Deep learning-based assessment of knee septic arthritis using transformer features in sonographic modalities.

Computer methods and programs in biomedicine
PURPOSE: Septic arthritis is an infectious disease. Conventionally, the diagnosis of septic arthritis can only be based on the identification of causal pathogens taken from synovial fluid, synovium or blood samples. However, the cultures require seve...

Exploring a deep learning neural architecture for closed Literature-based discovery.

Journal of biomedical informatics
Scientific literature presents a wealth of information yet to be explored. As the number of researchers increase with each passing year and publications are released, this contributes to an era where specialized fields of research are becoming more p...

Deep learning-based pathology signature could reveal lymph node status and act as a novel prognostic marker across multiple cancer types.

British journal of cancer
BACKGROUND: Identifying lymph node metastasis (LNM) relies mainly on indirect radiology. Current studies omitted the quantified associations with traits beyond cancer types, failing to provide generalisation performance across various tumour types.

Heart disease risk factors detection from electronic health records using advanced NLP and deep learning techniques.

Scientific reports
Heart disease remains the major cause of death, despite recent improvements in prediction and prevention. Risk factor identification is the main step in diagnosing and preventing heart disease. Automatically detecting risk factors for heart disease i...