AIMC Topic: Neural Networks, Computer

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[Establishment and clinical testing of pancreatic cancer Faster R-CNN AI system based on fast regional convolutional neural network].

Zhonghua wai ke za zhi [Chinese journal of surgery]
To investigate the effectiveness of an enhanced CT automatic recognition system based on Faster R-CNN for pancreatic cancer and its clinical value. In this study, 4 024 enhanced CT imaging sequences of 315 patients with pancreatic cancer from Janua...

Machine learning in haematological malignancies.

The Lancet. Haematology
Machine learning is a branch of computer science and statistics that generates predictive or descriptive models by learning from training data rather than by being rigidly programmed. It has attracted substantial attention for its many applications i...

Dr. Agent: Clinical predictive model via mimicked second opinions.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Prediction of disease phenotypes and their outcomes is a difficult task. In practice, patients routinely seek second opinions from multiple clinical experts for complex disease diagnosis. Our objective is to mimic such a practice of seekin...

Automatic Detection and Classification of Rib Fractures on Thoracic CT Using Convolutional Neural Network: Accuracy and Feasibility.

Korean journal of radiology
OBJECTIVE: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images.

An efficient approach based on multi-sources information to predict circRNA-disease associations using deep convolutional neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Emerging evidence indicates that circular RNA (circRNA) plays a crucial role in human disease. Using circRNA as biomarker gives rise to a new perspective regarding our diagnosing of diseases and understanding of disease pathogenesis. Howe...

Intelligent image-activated cell sorting 2.0.

Lab on a chip
The advent of intelligent image-activated cell sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells from heterogeneous populations. iIACS is an on-chip microfluidic technology that builds on a seamless inte...

An Efficient Method to Predict Pneumonia from Chest X-Rays Using Deep Learning Approach.

Studies in health technology and informatics
Pneumonia is a severe health problem causing millions of deaths every year. The aim of this study was to develop an advanced deep learning-based architecture to detect pneumonia using chest X-ray images. We utilized a convolutional neural network (CN...

Classification of Intracranial Hemorrhage Subtypes Using Deep Learning on CT Scans.

Studies in health technology and informatics
Intracranial hemorrhage is a pathological condition that requires fast diagnosis and decision making. Recently, a neural network model for classification of different intracranial hemorrhage types was proposed by a member of our research group Konsta...

Generation of Realistic Synthetic Validation Healthcare Datasets Using Generative Adversarial Networks.

Studies in health technology and informatics
BACKGROUND: Assurance of digital health interventions involves, amongst others, clinical validation, which requires large datasets to test the application in realistic clinical scenarios. Development of such datasets is time consuming and challenging...