AIMC Topic: Deep Learning

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Deep learning automatic segmentation and radiomics model for diagnosing pancreatic solid neoplasms in MRI.

BMC cancer
BACKGROUND: To develop and validate a deep learning tool for the automatic segmentation of pancreatic solid neoplasms and to establish a radiomics model for diagnosing these solid neoplasms in MRI.

Predicting outcomes in head and neck cancer using CT images via transfer learning.

BMC medical imaging
BACKGROUND: Accurate preoperative risk stratification for patients with head and neck (H&N) cancer remained a critical challenge, as long-term survival rates are poor despite aggressive multimodality treatment. While deep learning models showed promi...

A novel approach hybrid of ensemble learning and 3-D CNN mechanism: early-stage diagnosis of Alzheimer's disease using EEG signals.

Scientific reports
Alzheimer's disease (AD) is a progressive neurological disorder that causes brain cell degeneration and leads to dementia. Early and accurate detection of AD is crucial, as it allows timely treatment before the brain suffers permanent damage. In rece...

SpinachXAI-Rec: a multi-stage explainable AI framework for spinach freshness classification and consumer recommendation.

Scientific reports
Leafy vegetables such as spinach are among the most important components in a nutritious diet but are highly perishable and susceptible to premature spoilage. Traditional practices in determining freshness have been qualitative and time-consuming and...

An incremental adversarial training method enables timeliness and rapid new knowledge acquisition.

Scientific reports
Adversarial training is an effective defense method for deep models against adversarial attacks. However, current adversarial training methods require retraining the entire neural network, which consumes a significant amount of computational resource...

An innovative multi-head attention mechanism-driven recurrent neural network model with feature representation fusion for enhanced image captioning to assist individuals with visual impairments.

Scientific reports
Developments in image captioning technologies played a crucial role in improving the quality of life for individuals with visual impairments, advancing better social inclusivity. Image captioning is the task of representing the visual content of the ...

Enhanced brain tumor classification framework using deep learning.

Scientific reports
The increasing prevalence of brain tumors calls for the development of accurate and reliable diagnostic tools. Whereas traditional techniques offer some benefits, they can hardly detect or accurately classify the type of a tumor at an early stage, cr...

A comprehensive benchmark of single-cell Hi-C embedding tools.

Nature communications
Embedding is the key step in single-cell Hi-C (scHi-C) analysis which relies on capturing biological meaningful heterogeneity at various levels of genome architecture. To understand the strength and limitations of existing tools in various applicatio...

A deep learning-based framework for standardized analysis of trabecular bone compartments from micro-CT imaging data in the mouse tibia.

Scientific reports
Understanding bone remodeling and disease progression is crucial in preclinical skeletal research, particularly for assessing pharmacological and mechanical interventions in the long bones of murine models. High-resolution micro-computed tomography (...

Towards Robust Brain Midline Shift Detection: A YOLO-Based 3D Slicer Extension with a Novel Dataset.

Neuroinformatics
Accurate detection of brain midline shift is critical for the diagnosis and monitoring of neurological conditions such as traumatic brain injuries, strokes, and tumors. This study aims to address the lack of dedicated datasets and tools for this task...