AIMC Topic: Deep Learning

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The stability of oncologic MRI radiomic features and the potential role of deep learning: a review.

Physics in medicine and biology
The use of MRI radiomic models for the diagnosis, prognosis and treatment response prediction of tumors has been increasingly reported in literature. However, its widespread adoption in clinics is hampered by issues related to features stability. In ...

Smart Healthcare System with Light-Weighted Blockchain System and Deep Learning Techniques.

Computational intelligence and neuroscience
A radio communication sensor system is a collection of sensor modules that are connected to one another through wireless communication. It is common for them to be battery-powered and responsive to a nearby controller, referred to as the base station...

Online Course Model of Social and Political Education Using Deep Learning.

Computational intelligence and neuroscience
This study aims to improve the social and political literacy of college students. Social and Political Education (SPE) is studied for undergraduates. Firstly, the background of the subject research is introduced. The face recognition module is built ...

Deep Learning-Based Ultrasound Combined with Gastroscope for the Diagnosis and Nursing of Upper Gastrointestinal Submucous Lesions.

Computational and mathematical methods in medicine
The study focused on the diagnostic value of deep learning-based ultrasound combined with gastroscope examination for upper gastrointestinal submucous lesions and nursing. A total of 104 patients with upper gastrointestinal submucous lesions diagnose...

Joint optic disk and cup segmentation for glaucoma screening using a region-based deep learning network.

Eye (London, England)
OBJECTIVES: To develop and validate an end-to-end region-based deep convolutional neural network (R-DCNN) to jointly segment the optic disc (OD) and optic cup (OC) in retinal fundus images for precise cup-to-disc ratio (CDR) measurement and glaucoma ...

Deep learning-based fully automated body composition analysis of thigh CT: comparison with DXA measurement.

European radiology
OBJECTIVES: To compare volumetric CT with DL-based fully automated segmentation and dual-energy X-ray absorptiometry (DXA) in the measurement of thigh tissue composition.

Automatic hemorrhage segmentation on head CT scan for traumatic brain injury using 3D deep learning model.

Computers in biology and medicine
The most common cause of long-term disability and death in young adults is a traumatic brain injury. The decision for surgical intervention for craniotomy is dependent on the injury type and the patient's neurologic exam. The potential subtypes of in...

Automated estimation of total lung volume using chest radiographs and deep learning.

Medical physics
BACKGROUND: Total lung volume is an important quantitative biomarker and is used for the assessment of restrictive lung diseases.

Clinical evaluation of a deep learning model for segmentation of target volumes in breast cancer radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE/OBJECTIVE(S): Precise segmentation of clinical target volumes (CTV) in breast cancer is indispensable for state-of-the art radiotherapy. Despite international guidelines, significant intra- and interobserver variability exists, negatively imp...

An original deep learning model using limited data for COVID-19 discrimination: A multicenter study.

Medical physics
OBJECTIVES: Artificial intelligence (AI) has been proved to be a highly efficient tool for COVID-19 diagnosis, but the large data size and heavy label force required for algorithm development and the poor generalizability of AI algorithms, to some ex...