AIMC Topic: Deep Learning

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Deep learning applied to automatic disease detection using chest X-rays.

Journal of medical imaging and radiation oncology
Deep learning (DL) has shown rapid advancement and considerable promise when applied to the automatic detection of diseases using CXRs. This is important given the widespread use of CXRs across the world in diagnosing significant pathologies, and the...

Protein-Protein Interface Topology as a Predictor of Secondary Structure and Molecular Function Using Convolutional Deep Learning.

Journal of chemical information and modeling
To power the specific recognition and binding of protein partners into functional complexes, a wealth of information about the structure and function of the partners is necessarily encoded into the global shape of protein-protein interfaces and their...

4S-DT: Self-Supervised Super Sample Decomposition for Transfer Learning With Application to COVID-19 Detection.

IEEE transactions on neural networks and learning systems
Due to the high availability of large-scale annotated image datasets, knowledge transfer from pretrained models showed outstanding performance in medical image classification. However, building a robust image classification model for datasets with da...

A Robust Context-Based Deep Learning Approach for Highly Imbalanced Hyperspectral Classification.

Computational intelligence and neuroscience
Hyperspectral imaging is an area of active research with many applications in remote sensing, mineral exploration, and environmental monitoring. Deep learning and, in particular, convolution-based approaches are the current state-of-the-art classific...

Urine cell image recognition using a deep-learning model for an automated slide evaluation system.

BJU international
OBJECTIVES: To develop a classification system for urine cytology with artificial intelligence (AI) using a convolutional neural network algorithm that classifies urine cell images as negative (benign) or positive (atypical or malignant).

COVID-19 lesion detection and segmentation-A deep learning method.

Methods (San Diego, Calif.)
PURPOSE: In this paper, we utilized deep learning methods to screen the positive COVID-19 cases in chest CT. Our primary goal is to supply rapid and precise assistance for disease surveillance on the medical imaging aspect.

Intraoperative assessment of canine soft tissue sarcoma by deep learning enhanced optical coherence tomography.

Veterinary and comparative oncology
Soft tissue sarcoma (STS) is a locally aggressive and infiltrative tumour in dogs. Surgical resection is the treatment of choice for local tumour control. Currently, post-operative pathology is performed for surgical margin assessment. Spectral-domai...

Gait-Based Implicit Authentication Using Edge Computing and Deep Learning for Mobile Devices.

Sensors (Basel, Switzerland)
Implicit authentication mechanisms are expected to prevent security and privacy threats for mobile devices using behavior modeling. However, recently, researchers have demonstrated that the performance of behavioral biometrics is insufficiently accur...