AIMC Topic: Neural Networks, Computer

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Deceptive learning in histopathology.

Histopathology
AIMS: Deep learning holds immense potential for histopathology, automating tasks that are simple for expert pathologists and revealing novel biology for tasks that were previously considered difficult or impossible to solve by eye alone. However, the...

A novel decision support system for proactive risk management in healthcare based on fuzzy inference, neural network and support vector machine.

International journal of medical informatics
BACKGROUND: The nature of activities practiced in healthcare organizations makes risk management the most crucial issue for decision-makers, especially in developing countries. New technologies provide effective solutions to support engineers in mana...

Evaluating convolutional neural network-enhanced electrocardiography for hypertrophic cardiomyopathy detection in a specialized cardiovascular setting.

Heart and vessels
The efficacy of convolutional neural network (CNN)-enhanced electrocardiography (ECG) in detecting hypertrophic cardiomyopathy (HCM) and dilated HCM (dHCM) remains uncertain in real-world applications. This retrospective study analyzed data from 19,1...

Performance comparison of multifarious deep networks on caries detection with tooth X-ray images.

Journal of dentistry
OBJECTIVES: Deep networks have been preliminarily studied in caries diagnosis based on clinical X-ray images. However, the performance of different deep networks on caries detection is still unclear. This study aims to comprehensively compare the car...

STIRUnet: SwinTransformer and inverted residual convolution embedding in unet for Sea-Land segmentation.

Journal of environmental management
Extraction of coastline from optical remote sensing images is of paramount importance for coastal zone management, erosion monitoring, and intelligent ocean construction. However, nearshore marine environment complexity presents a challenge when capt...

AML leukocyte classification method for small samples based on ACGAN.

Biomedizinische Technik. Biomedical engineering
Leukemia is a class of hematologic malignancies, of which acute myeloid leukemia (AML) is the most common. Screening and diagnosis of AML are performed by microscopic examination or chemical testing of images of the patient's peripheral blood smear. ...

MV-SHIF: Multi-view symmetric hypothesis inference fusion network for emotion-cause pair extraction in documents.

Neural networks : the official journal of the International Neural Network Society
Emotion-cause pair extraction (ECPE) is a challenging task that aims to automatically identify pairs of emotions and their causes from documents. The difficulty of ECPE lies in distinguishing valid emotion-cause pairs from many irrelevant ones. Most ...

Deep learning-based glomerulus detection and classification with generative morphology augmentation in renal pathology images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Glomerulus morphology on renal pathology images provides valuable diagnosis and outcome prediction information. To provide better care, an efficient, standardized, and scalable method is urgently needed to optimize the time-consuming and labor-intens...

Multi-scale nested UNet with transformer for colorectal polyp segmentation.

Journal of applied clinical medical physics
BACKGROUND: Polyp detection and localization are essential tasks for colonoscopy. U-shape network based convolutional neural networks have achieved remarkable segmentation performance for biomedical images, but lack of long-range dependencies modelin...

Robustness evaluation of deep neural networks for endoscopic image analysis: Insights and strategies.

Medical image analysis
Computer-aided detection and diagnosis systems (CADe/CADx) in endoscopy are commonly trained using high-quality imagery, which is not representative for the heterogeneous input typically encountered in clinical practice. In endoscopy, the image quali...