AIMC Topic: Deep Learning

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Pathologist-level diagnosis of ulcerative colitis inflammatory activity level using an automated histological grading method.

International journal of medical informatics
BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) is a global disease that is evolving with increasing incidence. However, there are few works on computationally assisted diagnosis of IBD based on pathological images. Therefore, based on the UK a...

Bootstrap each lead's latent: A novel method for self-supervised learning of multilead electrocardiograms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Electrocardiogram (ECG) is one of the most important diagnostic tools for cardiovascular diseases (CVDs). Recent studies show that deep learning models can be trained using labeled ECGs to achieve automatic detection of CVDs...

Less is More: Selective reduction of CT data for self-supervised pre-training of deep learning models with contrastive learning improves downstream classification performance.

Computers in biology and medicine
BACKGROUND: Self-supervised pre-training of deep learning models with contrastive learning is a widely used technique in image analysis. Current findings indicate a strong potential for contrastive pre-training on medical images. However, further res...

Deep-learning classification of teat-end conditions in Holstein cattle.

Research in veterinary science
As a means of preventing mastitis, deep learning for classifying teat-end conditions in dairy cows has not yet been optimized. By using 1426 digital images of dairy cow udders, the extent of teat-end hyperkeratosis was assessed using a four-point sca...

Deep convolutional neural network-based identification and biological evaluation of MAO-B inhibitors.

International journal of biological macromolecules
Parkinson's disease (PD) is one of the most prominent motor disorder of adult-onset dementia connected to memory and other cognitive abilities. Individuals with this vicious neurodegenerative condition tend to have an elevated expression of Monoamine...

Deep learning to capture leaf shape in plant images: Validation by geometric morphometrics.

The Plant journal : for cell and molecular biology
Plant leaves play a pivotal role in automated species identification using deep learning (DL). However, achieving reproducible capture of leaf variation remains challenging due to the inherent "black box" problem of DL models. To evaluate the effecti...

A Deep Learning System to Predict Epithelial Dysplasia in Oral Leukoplakia.

Journal of dental research
Oral leukoplakia (OL) has an inherent disposition to develop oral cancer. OL with epithelial dysplasia (OED) is significantly likely to undergo malignant transformation; however, routine OED assessment is invasive and challenging. This study investig...

Evaluating Explainable Artificial Intelligence (XAI) techniques in chest radiology imaging through a human-centered Lens.

PloS one
The field of radiology imaging has experienced a remarkable increase in using of deep learning (DL) algorithms to support diagnostic and treatment decisions. This rise has led to the development of Explainable AI (XAI) system to improve the transpare...

Drug-Target Binding Affinity Prediction in a Continuous Latent Space Using Variational Autoencoders.

IEEE/ACM transactions on computational biology and bioinformatics
Accurate prediction of Drug-Target binding Affinity (DTA) is a daunting yet pivotal task in the sphere of drug discovery. Over the years, a plethora of deep learning-based DTA models have emerged, rendering promising results in predicting the binding...

TransC-ac4C: Identification of N4-Acetylcytidine (ac4C) Sites in mRNA Using Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
N4-acetylcytidine (ac4C) is a post-transcriptional modification in mRNA that is critical in mRNA translation in terms of stability and regulation. In the past few years, numerous approaches employing convolutional neural networks (CNN) and Transforme...