AIMC Topic: Deep Learning
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Deep learning for orbital fracture detection and reconstruction: A systematic review on diagnostic accuracy and surgical planning.
Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Jun 17, 2025
OBJECTIVE: To systematically review the efficacy of deep learning (DL) models in detecting and reconstructing orbital fractures based on computed tomography (CT) imaging, assessing their diagnostic accuracy, processing time, and role in surgical plan...
Automated sex and age estimation from orthopantomograms using deep learning: A comparison with human predictions.
Forensic science international
Jun 17, 2025
INTRODUCTION/OBJECTIVES: Estimating sex and chronological age is crucial in forensic dentistry and forensic identification. Traditional manual methods for sex and age estimation are labor-intensive, time-consuming, and prone to errors. This study aim...
Deep learning based colorectal cancer detection in medical images: A comprehensive analysis of datasets, methods, and future directions.
Clinical imaging
Jun 17, 2025
This comprehensive review examines the current state and evolution of artificial intelligence applications in colorectal cancer detection through medical imaging from 2019 to 2025. The study presents a quantitative analysis of 110 high-quality public...
Patch-type wearable electrocardiography and impedance pneumography for sleep staging: A multi-modal deep learning approach.
Computers in biology and medicine
Jun 17, 2025
Sleep staging is critical for investigating sleep quality and detecting disorders. Polysomnography (PSG) remains the gold standard, but is costly and impractical for routine monitoring. This study evaluates the feasibility of a patch-type wearable de...
NLP-like deep learning aided in identification and validation of thiosulfinate tolerance clusters in diverse bacteria.
mSphere
Jun 17, 2025
Allicin tolerance () clusters in phytopathogenic bacteria, which provide resistance to thiosulfinates like allicin, are challenging to find using conventional approaches due to their varied architecture and the paradox of being vertically maintained ...
Exploratory multi-cohort, multi-reader study on the clinical utility of a deep learning model for transforming cryosectioned to formalin-fixed, paraffin-embedded (FFPE) images in breast lesion diagnosis.
Breast cancer research : BCR
Jun 17, 2025
BACKGROUND: Cryosectioned tissues often exhibit artifacts that compromise pathologists' diagnostic accuracy during intraoperative assessments. These inconsistencies, compounded by variations in frozen section (FS) production across laboratories, high...
Identifying and predicting EEG microstates with sequence-to-sequence deep learning models for online applications.
Journal of neural engineering
Jun 17, 2025
Electroencephalographic (EEG) microstates, as a non-invasive and high-temporal-resolution tool for analyzing time-space features of brain activity, have been validated and applied in various research domains. However, current methods for EEG microsta...
Enhancing image quality in fast neutron-based range verification of proton therapy using a deep learning-based prior in LM-MAP-EM reconstruction.
Physics in medicine and biology
Jun 17, 2025
This study investigates the use of list-mode (LM) maximum(MAP) expectation maximization (EM) incorporating prior information predicted by a convolutional neural network for image reconstruction in fast neutron (FN)-based proton therapy range verifica...
High-definition motion-resolved MRI using 3D radial kooshball acquisition and deep learning spatial-temporal 4D reconstruction.
Physics in medicine and biology
Jun 17, 2025
To develop motion-resolved volumetric MRI with 1.1 mm isotropic resolution and scan times <5 min using a combination of 3D radial kooshball acquisition and spatial-temporal deep learning 4D reconstruction for free-breathing high-definition (HD) lung ...
Arrhythmia classification based on multi-input convolutional neural network with attention mechanism.
PloS one
Jun 17, 2025
Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and cardiac arrest. While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variabi...
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