AIMC Topic: Neural Networks, Computer

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Performance of deep learning models for the classification and object detection of different oral white lesions using photographic images.

Scientific reports
Computer vision adjunctive technology for oral lesion diagnoses has been developed to detect and identify Oral Potentially Malignant Disorders (OPMDs) and non-OPMDs. The early detection of OPMDs can reduce the risk of oral cancer development, improvi...

Development and verification of a convolutional neural network-based model for automatic mandibular canal localization on multicenter CBCT images.

BMC oral health
OBJECTIVES: Development and verification of a convolutional neural network (CNN)-based deep learning (DL) model for mandibular canal (MC) localization on multicenter cone beam computed tomography (CBCT) images.

GNODEVAE: a graph-based ODE-VAE enhances clustering for single-cell data.

BMC genomics
BACKGROUND: Single-cell RNA sequencing analysis faces critical challenges including high dimensionality, sparsity, and complex topological relationships between cells. Current methods struggle to simultaneously preserve global structure, model cellul...

A lightweight and explainable CNN model for empowering plant disease diagnosis.

Scientific reports
Crop disease is a significant challenge in agriculture, requiring quick and precise detection to safeguard yields and reduce economic losses. Traditional diagnostic methods are slow, labor-intensive, and rely on expert knowledge, limiting scalability...

Integrating non-linear radon transformation for diabetic retinopathy grading.

Scientific reports
Diabetic retinopathy is a serious ocular complication that poses a significant threat to patients' vision and overall health. Early detection and accurate grading are essential to prevent vision loss. Current automatic grading methods rely heavily on...

Deep Learning for the Early Detection of Invasive Ductal Carcinoma in Histopathological Images: Convolutional Neural Network Approach With Transfer Learning.

JMIR formative research
BACKGROUND: Invasive ductal carcinoma (IDC) is considered the most common form of breast cancer, accounting for a significant percentage of mortality worldwide. Therefore, its early detection is vital to further improve patients' outcomes and surviva...

Assessment of plant diversity index in degraded desert grassland using UAV hyperspectral multimodal data and Encoder-CNN.

Scientific reports
The biodiversity function of the desert steppe ecosystem faces many challenges under the pressure of climate change and human activities. Accurate and efficient assessment of plant diversity is critical for guiding desert steppe restoration efforts. ...

Predicting knee osteoarthritis progression using neural network with longitudinal MRI radiomics, and biochemical biomarkers: A modeling study.

PLoS medicine
BACKGROUND: Knee osteoarthritis (KOA) worsens both structurally and symptomatically, yet no model predicts KOA progression using Magnetic Resonance Image (MRI) radiomics and biomarkers. This study aimed to develop and test the longitudinal Load-Beari...

Navigating tenses in Bengali sentences: A stacked ensemble model for enhanced prediction.

PloS one
Tense classification in Bengali sentences is a fundamental yet unsolved problem of Bangla natural language processing (NLP) which is essential for tasks like machine translation, sentiment analysis, grammar correction, writing assistance and sentence...

Predicting art university students' entrepreneurial intention: A hybrid SEM-ANN approach.

PloS one
In recent years, academics and policymakers have increasingly focused on entrepreneurial behavior among university students. While existing studies have explored the entrepreneurial intention (EI) of students from various academic disciplines, few ha...