AIMC Topic: Deep Learning

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Deep fuzzy physics-informed neural networks for forward and inverse PDE problems.

Neural networks : the official journal of the International Neural Network Society
As a grid-independent approach for solving partial differential equations (PDEs), Physics-Informed Neural Networks (PINNs) have garnered significant attention due to their unique capability to simultaneously learn from both data and the governing phy...

ChatDiff: A ChatGPT-based diffusion model for long-tailed classification.

Neural networks : the official journal of the International Neural Network Society
Long-tailed data distributions have been a major challenge for the practical application of deep learning. Information augmentation intends to expand the long-tailed data into uniform distribution, which provides a feasible way to mitigate the data s...

Predicting pedestrian-vehicle interaction severity at unsignalized intersections.

Traffic injury prevention
OBJECTIVES: This study aims to develop and validate a novel deep-learning model that predicts the severity of pedestrian-vehicle interactions at unsignalized intersections, distinctively integrating Transformer-based models with Multilayer Perceptron...

How the technologies behind self-driving cars, social networks, ChatGPT, and DALL-E2 are changing structural biology.

BioEssays : news and reviews in molecular, cellular and developmental biology
The performance of deep Neural Networks (NNs) in the text (ChatGPT) and image (DALL-E2) domains has attracted worldwide attention. Convolutional NNs (CNNs), Large Language Models (LLMs), Denoising Diffusion Probabilistic Models (DDPMs)/Noise Conditio...

Early cancer detection using deep learning and medical imaging: A survey.

Critical reviews in oncology/hematology
Cancer, characterized by the uncontrolled division of abnormal cells that harm body tissues, necessitates early detection for effective treatment. Medical imaging is crucial for identifying various cancers, yet its manual interpretation by radiologis...

Artificial intelligence and radiotherapy: Evolution or revolution?

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
The integration of artificial intelligence, particularly deep learning algorithms, into radiotherapy represents a transformative shift in the field, enhancing accuracy, efficiency, and personalized care. This paper explores the multifaceted impact of...

Path of career planning and employment strategy based on deep learning in the information age.

PloS one
With the improvement of education level and the expansion of higher education, more students can have the opportunities to obtain better education, and the pressure of employment competition is also increasing. How to improve students' employment com...

BCCHI-HCNN: Breast Cancer Classification from Histopathological Images Using Hybrid Deep CNN Models.

Journal of imaging informatics in medicine
Breast cancer is the most common cancer in women globally, imposing a significant burden on global public health due to high death rates. Data from the World Health Organization show an alarming annual incidence of nearly 2.3 million new cases, drawi...

Deep Learning-Based Estimation of Radiographic Position to Automatically Set Up the X-Ray Prime Factors.

Journal of imaging informatics in medicine
Radiation dose and image quality in radiology are influenced by the X-ray prime factors: KVp, mAs, and source-detector distance. These parameters are set by the X-ray technician prior to the acquisition considering the radiographic position. A wrong ...

A smartphone-integrated deep learning strategy-assisted rapid detection system for monitoring dual-modal immunochromatographic assay.

Talanta
This study focuses on the integration of a custom-built and optimally trained YOLO v5 model into a smartphone app developed with Java language. A dual-modal immunochromatographic rapid detection system based on a deep learning strategy for smartphone...