AIMC Topic: Deep Learning
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A deep learning detection method for pancreatic cystic neoplasm based on Mamba architecture.
Journal of X-ray science and technology
Feb 18, 2025
OBJECTIVE: Early diagnosis of pancreatic cystic neoplasm (PCN) is crucial for patient survival. This study proposes M-YOLO, a novel model combining Mamba architecture and YOLO, to enhance the detection of pancreatic cystic tumors. The model addresses...
Deep Learning Protocol for Predicting Full-Spectrum Infrared and Raman Spectra of Polypeptides and Proteins Using All-Atom Models.
The journal of physical chemistry letters
Feb 18, 2025
Infrared (IR) spectroscopy and Raman spectroscopy are powerful tools for probing protein and peptide structures due to their capability to provide molecular fingerprints. As a popular spectral simulation method, the quantum chemistry (QC) calculation...
Deep learning-based automated guide for defining a standard imaging plane for developmental dysplasia of the hip screening using ultrasonography: a retrospective imaging analysis.
BMC medical informatics and decision making
Feb 18, 2025
BACKGROUND: We aimed to propose a deep-learning neural network model for automatically detecting five landmarks during a two-dimensional (2D) ultrasonography (US) scan to develop a standard plane for developmental dysplasia of the hip (DDH) screening...
Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatch.
Scientific reports
Feb 18, 2025
The presence of a diffusion-weighted imaging (DWI)-fluid-attenuated inversion recovery (FLAIR) mismatch holds potential value in identifying candidates for recanalization treatment. However, the visual assessment of DWI-FLAIR mismatch is subject to l...
HDL-ACO hybrid deep learning and ant colony optimization for ocular optical coherence tomography image classification.
Scientific reports
Feb 18, 2025
Optical Coherence Tomography (OCT) plays a crucial role in diagnosing ocular diseases, yet conventional CNN-based models face limitations such as high computational overhead, noise sensitivity, and data imbalance. This paper introduces HDL-ACO, a nov...
Hybrid Greylag Goose deep learning with layered sparse network for women nutrition recommendation during menstrual cycle.
Scientific reports
Feb 18, 2025
A complex biological process involves physical changes and hormonal fluctuation in the menstrual cycle. The traditional nutrition recommendation models often offer general guidelines but fail to address the specific requirements of women during vario...
Linear regressive weighted Gaussian kernel liquid neural network for brain tumor disease prediction using time series data.
Scientific reports
Feb 18, 2025
A brain tumor is an abnormal growth of cells within the brain or surrounding tissues, which can be either benign or malignant. Brain tumors develop in various regions of the brain, each affecting different functions such as movement, speech, and visi...
Applying deep learning and the ecological home range concept to document the spatial distribution of Atlantic salmon parr (Salmo salar L.) in experimental tanks.
Scientific reports
Feb 18, 2025
Measuring and monitoring fish welfare in aquaculture research relies on the use of outcome- (biotic) and input-based (e.g., abiotic) welfare indicators (WIs). Incorporating behavioural auditing into this toolbox can sometimes be challenging because s...
Accelerating veterinary low field MRI acquisitions using the deep learning based denoising solution HawkAI.
Scientific reports
Feb 18, 2025
Magnetic resonance imaging (MRI) has changed veterinary diagnosis but its long-sequence time can be problematic, especially because animals need to be sedated during the exam. Unfortunately, shorter scan times implies a fall in overall image quality ...
Enhancing diabetic retinopathy diagnosis: automatic segmentation of hyperreflective foci in OCT via deep learning.
International ophthalmology
Feb 18, 2025
OBJECTIVE: Hyperreflective foci (HRF) are small, punctate lesions ranging from 20 to 50 m and exhibiting high reflective intensity in optical coherence tomography (OCT) images of patients with diabetic retinopathy (DR). The purpose of the model prop...
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