AIMC Topic: Deep Learning

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Artificial Intelligence Enterprise Management Using Deep Learning.

Computational intelligence and neuroscience
In this paper, we explore the application status of deep learning (DL) in enterprise management, with China Merchants Bank as an example, and the role of DL in bank enterprise management. We analysed the application status of AI in marketing, risk co...

Wushu Routine Movement and Diagnosis Based on Deep Learning and Symmetric Difference Algorithm.

Computational intelligence and neuroscience
Wushu is one of the traditional cultural symbols of the Chinese nation. It is also one of the most popular sports activities among the people. With the attention and love of contemporary people to sports activities, Wushu is also constantly developin...

Recognition and Segmentation of Individual Bone Fragments with a Deep Learning Approach in CT Scans of Complex Intertrochanteric Fractures: A Retrospective Study.

Journal of digital imaging
The characteristics of bone fragments are the main influencing factors for the choice of treatment in intertrochanteric fractures. This study aimed to develop a deep learning algorithm for recognizing and segmenting individual fragments in CT images ...

Microarchitectural Changes of Cardiovascular Calcification in Response to In Vivo Interventions Using Deep-Learning Segmentation and Computed Tomography Radiomics.

Arteriosclerosis, thrombosis, and vascular biology
BACKGROUND: Coronary calcification associates closely with cardiovascular risk, but its progress is accelerated in response to some interventions widely used to reduce risk. This paradox suggests that qualitative, not just quantitative, changes in ca...

Weakly supervised deep learning for prediction of treatment effectiveness on ovarian cancer from histopathology images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Despite the progress made during the last two decades in the surgery and chemotherapy of ovarian cancer, more than 70 % of advanced patients are with recurrent cancer and decease. Surgical debulking of tumors following chemotherapy is the conventiona...

Deep Learning Framework for Integrating Multibatch Calibration, Classification, and Pathway Activities.

Analytical chemistry
The amount of available biological data has exploded since the emergence of high-throughput technologies, which is not only revolting the way we recognize molecules and diseases but also bringing novel analytical challenges to bioinformatics analysis...

Systems Drug Discovery for Diffuse Large B Cell Lymphoma Based on Pathogenic Molecular Mechanism via Big Data Mining and Deep Learning Method.

International journal of molecular sciences
Diffuse large B cell lymphoma (DLBCL) is an aggressive heterogeneous disease. The most common subtypes of DLBCL include germinal center b-cell (GCB) type and activated b-cell (ABC) type. To learn more about the pathogenesis of two DLBCL subtypes (i.e...

RA V-Net: deep learning network for automated liver segmentation.

Physics in medicine and biology
Segmenting liver from CT images is the first step for doctors to diagnose a patient's disease. Processing medical images with deep learning models has become a current research trend. Although it can automate segmenting region of interest of medical ...

Deep Learning Versus Traditional Solutions for Group Trajectory Outliers.

IEEE transactions on cybernetics
This article introduces a new model to identify a group of trajectory outliers from a large trajectory database and proposes several algorithms. These can be split into three categories: 1) algorithms based on data mining and knowledge discovery, whi...