AIMC Topic: Databases, Factual

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SpeckleGAN: a generative adversarial network with an adaptive speckle layer to augment limited training data for ultrasound image processing.

International journal of computer assisted radiology and surgery
PURPOSE: In the field of medical image analysis, deep learning methods gained huge attention over the last years. This can be explained by their often improved performance compared to classic explicit algorithms. In order to work well, they need larg...

Optimal length of R-R interval segment window for Lorenz plot detection of paroxysmal atrial fibrillation by machine learning.

Biomedical engineering online
BACKGROUND: Heartbeat interval Lorenz plot (LP) imaging is a promising method for detecting atrial fibrillation (AF) in long-term monitoring, but the optimal segment window length for the LP images is unknown. We examined the performance of AF detect...

Artificial Intelligence Medical Ultrasound Equipment: Application of Breast Lesions Detection.

Ultrasonic imaging
Breast cancer ranks first among cancers affecting women's health. Our work aims to realize the intelligence of the medical ultrasound equipment with limited computational capability, which is used for the assistant detection of breast lesions. We emb...

Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading.

Virchows Archiv : an international journal of pathology
The International Society of Urological Pathology (ISUP) hosts a reference image database supervised by experts with the purpose of establishing an international standard in prostate cancer grading. Here, we aimed to identify areas of grading difficu...

Convolutional neural network for detection and classification of seizures in clinical data.

Medical & biological engineering & computing
Epileptic seizure detection and classification in clinical electroencephalogram data still is a challenge, and only low sensitivity with a high rate of false positives has been achieved with commercially available seizure detection tools, which usual...

Recurrent convolutional neural kernel model for stock price movement prediction.

PloS one
Stock price movement prediction plays important roles in decision making for investors. It was usually regarded as a binary classification task. In this paper, a recurrent convolutional neural kernel (RCNK) model was proposed, which learned complemen...

Machine-learning-based diagnostics of EEG pathology.

NeuroImage
Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with handcrafted features), and end-to-end approaches (with learned features). Previous studies on EEG pathology decoding ...

Analyzing Factors Associated with Fatal Road Crashes: A Machine Learning Approach.

International journal of environmental research and public health
Road traffic injury accounts for a substantial human and economic burden globally. Understanding risk factors contributing to fatal injuries is of paramount importance. In this study, we proposed a model that adopts a hybrid ensemble machine learning...