AIMC Topic: Deep Learning
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Development of model for identifying homologous recombination deficiency (HRD) status of ovarian cancer with deep learning on whole slide images.
Journal of translational medicine
Mar 4, 2025
BACKGROUND: Homologous recombination deficiency (HRD) refers to the dysfunction of homologous recombination repair (HRR) at the cellular level. The assessment of HRD status has the important significance for the formulation of treatment plans, effica...
Automated classification of chest X-rays: a deep learning approach with attention mechanisms.
BMC medical imaging
Mar 4, 2025
BACKGROUND: Pulmonary diseases such as COVID-19 and pneumonia, are life-threatening conditions, that require prompt and accurate diagnosis for effective treatment. Chest X-ray (CXR) has become the most common alternative method for detecting pulmonar...
Evolution of AI enabled healthcare systems using textual data with a pretrained BERT deep learning model.
Scientific reports
Mar 4, 2025
In the rapidly evolving field of healthcare, Artificial Intelligence (AI) is increasingly driving the promotion of the transformation of traditional healthcare and improving medical diagnostic decisions. The overall goal is to uncover emerging trends...
An Efficient Approach for Detection of Various Epileptic Waves Having Diverse Forms in Long Term EEG Based on Deep Learning.
Brain topography
Mar 4, 2025
EEG is the most powerful tool for epilepsy discharge detection in brain. Visual evaluation is hard in long term monitoring EEG data as huge amount of data needs to be inspected. Considering the fast and efficient results from deep learning networks e...
Sugarcane leaf disease classification using deep neural network approach.
BMC plant biology
Mar 4, 2025
OBJECTIVE: The objective is to develop a reliable deep learning (DL) based model that can accurately diagnose diseases. It seeks to address the challenges posed by the traditional approach of manually diagnosing diseases to enhance the control of dis...
Deep learning-assisted identification and localization of ductal carcinoma from bulk tissue in-silico models generated through polarized Monte Carlo simulations.
Biomedical physics & engineering express
Mar 4, 2025
Despite significant progress in diagnosis and treatment, breast cancer remains a formidable health challenge, emphasizing the continuous need for research. This simulation study uses polarized Monte Carlo approach to identify and locate breast cancer...
Deep Learning-Based ASPECTS Algorithm Enhances Reader Performance and Reduces Interpretation Time.
AJNR. American journal of neuroradiology
Mar 4, 2025
BACKGROUND AND PURPOSE: ASPECTS is a long-standing and well-documented selection criterion for acute ischemic stroke treatment; however, the interpretation of ASPECTS is a challenging and time-consuming task for physicians with notable interobserver ...
Prediction of Lymph Node Metastasis in Lung Cancer Using Deep Learning of Endobronchial Ultrasound Images With Size on CT and PET-CT Findings.
Respirology (Carlton, Vic.)
Mar 3, 2025
BACKGROUND AND OBJECTIVE: Echo features of lymph nodes (LNs) influence target selection during endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA). This study evaluates deep learning's diagnostic capabilities on EBUS images f...
Deep learning-aided preparation and mechanism revaluation of waste wood lignocellulose-based flame-retardant composites.
International journal of biological macromolecules
Mar 3, 2025
Wood and its derivatives play a decisive role in traditional Chinese architecture. Waste wood as a major source of garbage in the construction industry represents a valuable source. The efficient recycling of waste wood has become an urgent technical...
Deep learning based image enhancement for dynamic non-Cartesian MRI: Application to "silent" fMRI.
Computers in biology and medicine
Mar 3, 2025
Radial based non-Cartesian sequences may be used for silent functional MRI examinations particularly in settings where scanner noise could pose issues. However, to achieve reasonable temporal resolution, under-sampled 3D radial k-space commonly resul...
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