AIMC Topic: Databases, Factual

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Modified osprey algorithm for optimizing capsule neural network in leukemia image recognition.

Scientific reports
The diagnosis of leukemia is a serious matter that requires immediate and accurate attention. This research presents a revolutionary method for diagnosing leukemia using a Capsule Neural Network (CapsNet) with an optimized design. CapsNet is a cuttin...

Dual-Channel Prototype Network for Few-Shot Pathology Image Classification.

IEEE journal of biomedical and health informatics
In the field of pathology, the scarcity of certain diseases and the difficulty of annotating images hinder the development of large, high-quality datasets, which in turn affects the advancement of deep learning-assisted diagnostics. Few-shot learning...

Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalization.

IEEE transactions on medical imaging
Fairness (also known as equity interchangeably) in machine learning is important for societal well-being, but limited public datasets hinder its progress. Currently, no dedicated public medical datasets with imaging data for fairness learning are ava...

Multi-Grained Radiology Report Generation With Sentence-Level Image-Language Contrastive Learning.

IEEE transactions on medical imaging
The automatic generation of accurate radiology reports is of great clinical importance and has drawn growing research interest. However, it is still a challenging task due to the imbalance between normal and abnormal descriptions and the multi-senten...

Shape-Scale Co-Awareness Network for 3D Brain Tumor Segmentation.

IEEE transactions on medical imaging
The accurate segmentation of brain tumor is significant in clinical practice. Convolutional Neural Network (CNN)-based methods have made great progress in brain tumor segmentation due to powerful local modeling ability. However, brain tumors are freq...

The analysis of the internet of things database query and optimization using deep learning network model.

PloS one
To explore the application effect of the deep learning (DL) network model in the Internet of Things (IoT) database query and optimization. This study first analyzes the architecture of IoT database queries, then explores the DL network model, and fin...

NeurostimML: a machine learning model for predicting neurostimulation-induced tissue damage.

Journal of neural engineering
. The safe delivery of electrical current to neural tissue depends on many factors, yet previous methods for predicting tissue damage rely on only a few stimulation parameters. Here, we report the development of a machine learning approach that could...

VascuConNet: an enhanced connectivity network for vascular segmentation.

Medical & biological engineering & computing
Medical image segmentation commonly involves diverse tissue types and structures, including tasks such as blood vessel segmentation and nerve fiber bundle segmentation. Enhancing the continuity of segmentation outcomes represents a pivotal challenge ...

Bluish veil detection and lesion classification using custom deep learnable layers with explainable artificial intelligence (XAI).

Computers in biology and medicine
Melanoma, one of the deadliest types of skin cancer, accounts for thousands of fatalities globally. The bluish, blue-whitish, or blue-white veil (BWV) is a critical feature for diagnosing melanoma, yet research into detecting BWV in dermatological im...

Building a challenging medical dataset for comparative evaluation of classifier capabilities.

Computers in biology and medicine
Since the 2000s, digitalization has been a crucial transformation in our lives. Nevertheless, digitalization brings a bulk of unstructured textual data to be processed, including articles, clinical records, web pages, and shared social media posts. A...