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Pterygium Screening and Lesion Area Segmentation Based on Deep Learning.

Journal of healthcare engineering
A two-category model and a segmentation model of pterygium were proposed to assist ophthalmologists in establishing the diagnosis of ophthalmic diseases. A total of 367 normal anterior segment images and 367 pterygium anterior segment images were col...

Extravasation Screening and Severity Prediction from Skin Lesion Image using Deep Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Extravasation occurs secondary to the leakage of medication from blood vessels into the surrounding tissue during intravenous administration resulting in significant soft tissue injury and necrosis. If treatment is delayed, invasive management such a...

Stiffness Adaptation of a Hybrid Soft Surgical Robot for Improved Safety in Interventional Surgery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Minimally invasive instruments are inserted per-cutaneously and are steered toward the desired anatomy. The low stiffness of instruments is an advantage; however, once the target is reached, the instrument usually is required to transmit force to the...

Artificial intelligence in histopathology: enhancing cancer research and clinical oncology.

Nature cancer
Artificial intelligence (AI) methods have multiplied our capabilities to extract quantitative information from digital histopathology images. AI is expected to reduce workload for human experts, improve the objectivity and consistency of pathology re...

CNN-based two-branch multi-scale feature extraction network for retrosynthesis prediction.

BMC bioinformatics
BACKGROUND: Retrosynthesis prediction is the task of deducing reactants from reaction products, which is of great importance for designing the synthesis routes of the target products. The product molecules are generally represented with some descript...

Breast cancer detection and classification in mammogram using a three-stage deep learning framework based on PAA algorithm.

Artificial intelligence in medicine
In recent years, deep learning has been used to develop an automatic breast cancer detection and classification tool to assist doctors. In this paper, we proposed a three-stage deep learning framework based on an anchor-free object detection algorith...

SurvivalCNN: A deep learning-based method for gastric cancer survival prediction using radiological imaging data and clinicopathological variables.

Artificial intelligence in medicine
Radiological images have shown promising effects in patient prognostication. Deep learning provides a powerful approach for in-depth analysis of imaging data and integration of multi-modal data for modeling. In this work, we propose SurvivalCNN, a de...

Application of deep learning-based diagnostic systems in screening asymptomatic COVID-19 patients among oversea returnees.

Journal of infection in developing countries
INTRODUCTION: Our study aimed to investigate the performance of deep learning (DL)-based diagnostic systems in alerting against COVID-19, especially among asymptomatic individuals coming from overseas, and to analyze the features of identified asympt...

Framework for Vehicle Make and Model Recognition-A New Large-Scale Dataset and an Efficient Two-Branch-Two-Stage Deep Learning Architecture.

Sensors (Basel, Switzerland)
In recent years, Vehicle Make and Model Recognition (VMMR) has attracted a lot of attention as it plays a crucial role in Intelligent Transportation Systems (ITS). Accurate and efficient VMMR systems are required in real-world applications including ...