AIMC Topic: Deep Learning

Clear Filters Showing 1781 to 1790 of 26499 articles

A robust deep learning framework for multiclass skin cancer classification.

Scientific reports
Skin cancer represents a significant global health concern, where early and precise diagnosis plays a pivotal role in improving treatment efficacy and patient survival rates. Nonetheless, the inherent visual similarities between benign and malignant ...

Identifying invasiveness to aid lung adenocarcinoma diagnosis using deep learning and pathomics.

Scientific reports
Most classification efforts for primary subtypes of lung adenocarcinoma (LUAD) have not yet been integrated into clinical practice. This study explores the feasibility of combining deep learning and pathomics to identify tumor invasiveness in LUAD pa...

Human sleep position classification using a lightweight model and acceleration data.

Sleep & breathing = Schlaf & Atmung
PURPOSE: This exploratory study introduces a portable, wearable device using a single accelerometer to monitor twelve sleep positions. Targeted for home use, the device aims to assist patients with mild conditions such as gastroesophageal reflux dise...

PhysioEx: a new Python library for explainable sleep staging through deep learning.

Physiological measurement
Sleep staging is a crucial task in clinical and research contexts for diagnosing and understanding sleep disorders. This work introduces PhysioEx (Physiological Signal Explainer), a Python library designed to support the analysis of sleep stages usin...

Scaling Synthetic Brain Data Generation.

IEEE journal of biomedical and health informatics
The limited availability of diverse, high-quality datasets is a significant challenge in applying deep learning to neuroimaging research. Although synthetic data generation can potentially address this issue, on-the-fly generation is computationally ...

WaveSleepNet: An Interpretable Network for Expert-Like Sleep Staging.

IEEE journal of biomedical and health informatics
Although deep learning algorithms have proven their efficiency in automatic sleep staging, their "black-box" nature has limited their clinical adoption. In this study, we propose WaveSleepNet, an interpretable neural network for sleep staging that re...

EDSRNet: An Enhanced Decoder Semantic Recovery Network for 2D Medical Image Segmentation.

IEEE journal of biomedical and health informatics
In recent years, with the advancement of medical imaging technology, medical image segmentation has played a key role in assisting diagnosis and treatment planning. Current deep learning-based medical image segmentation methods mainly adopt encoder-d...

CT-Less Whole-Body Bone Segmentation of PET Images Using a Multimodal Deep Learning Network.

IEEE journal of biomedical and health informatics
In bone cancer imaging, positron emission tomography (PET) is ideal for the diagnosis and staging of bone cancers due to its high sensitivity to malignant tumors. The diagnosis of bone cancer requires tumor analysis and localization, where accurate a...

PFPRNet: A Phase-Wise Feature Pyramid With Retention Network for Polyp Segmentation.

IEEE journal of biomedical and health informatics
Early detection of colonic polyps is crucial for the prevention and diagnosis of colorectal cancer. Currently, deep learning-based polyp segmentation methods have become mainstream and achieved remarkable results. Acquiring a large number of labeled ...

DSANIB: Drug-Target Interaction Predictions With Dual-View Synergistic Attention Network and Information Bottleneck Strategy.

IEEE journal of biomedical and health informatics
Prediction of drug-target interactions (DTIs) is one of the crucial steps for drug repositioning. Identifying DTIs through bio-experimental manners is always expensive and time-consuming. Recently, deep learning-based approaches have shown promising ...