AIMC Topic: Deep Learning

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A robust artificial intelligence system for predicting EBV status in gastric cancer biopsy and resection specimens.

Scientific reports
Epstein-Barr virus (EBV) associated gastric cancer, accounting for ~ 9% of all gastric cancers, has unique pathologic, genomic, and clinical features and is linked to a better prognosis. Therefore, we aim to develop and validate a robust deep learnin...

Multi-task deep learning framework combining CNN: vision transformers and PSO for accurate diabetic retinopathy diagnosis and lesion localization.

Scientific reports
Diabetic Retinopathy (DR) continues to be the leading cause of preventable blindness worldwide, and there is an urgent need for accurate and interpretable framework. A Multi View Cross Attention Vision Transformer (MVCAViT) framework is proposed in t...

Enhancing peptide identification in metaproteomics through curriculum learning in deep learning.

Nature communications
Metaproteomics offers a powerful window into the active functions of microbial communities, but accurately identifying peptides remains challenging due to the size and incompleteness of protein databases derived from metagenomes. These databases ofte...

Automatic differentiation of voluntary and tremulous motion using ensemble empirical mode decomposition and convolutional Bi-directional LSTM.

Scientific reports
To develop applications for assisting Parkinson's disease (PD) patients, extracting Parkinsonian tremors from the raw signal is crucial; however, conventional methods such as filtering require a preset frequency range, and a poorly set frequency rang...

Assessing the risk of recurrence in early-stage breast cancer through H&E stained whole slide images.

Scientific reports
Accurate prediction of the likelihood of recurrence is important in the selection of postoperative treatment for patients with early-stage breast cancer. In this study, we investigated whether deep learning algorithms can predict patients' risk of re...

Opportunistic screening of low bone mass using knowledge distillation-based deep learning in chest X-rays with external validations.

Archives of osteoporosis
UNLABELLED: Low bone mass (LBM), which can lead to osteoporosis, is often undetected and increases the risk of bone fractures. This study presents OsPenScreen, a deep learning model that can identify low bone mass early using standard chest X-rays (C...

Revisiting Challenges in Real-world Video Colonoscopy using End-to-End Two Stream Polyp Detection Transformer (TS-PDTR).

Journal of medical systems
Accurate polyp detection is essential for the early diagnosis and effective treatment of colorectal cancer (CRC). However, colonoscopy videos in real-world clinical settings present significant challenges, often causing existing algorithms to fail. C...

High-content high-resolution microscopy and deep learning-assisted analysis reveals host and bacterial heterogeneity during infection.

eLife
is a Gram-negative bacterial pathogen and causative agent of bacillary dysentery. is closely related to but harbours a virulence plasmid that encodes a type III secretion system (T3SS) required for host cell invasion. Widely recognised as a paradi...

Optimized hybrid RNN-GRU model for predictive diagnosis of cardiovascular disease.

Biomedical physics & engineering express
Cardiovascular disease (CVD) continues to be the leading cause of death for individuals all over the globe, and India bears a disproportionate share of the burden associated with this condition. A hybrid deep learning model that combines Recurrent Ne...

Gait recognition using spatio-temporal representation fusion learning network with IMU-based skeleton graph and body partition strategy.

PloS one
The precise recognition of human lower limb movements based on wearable sensors is very important for human-computer interaction. However, the existing methods tend to ignore the dynamic spatial information in the process of executing human lower lim...