Multi-model deep learning approach for segmentation of teeth and periapical lesions on pantomographs
Introduction The fields of medicine and dentistry are beginning to integrate artificial
intelligence (AI) in diagnostics. This may reduce subjectivity and improve the accuracy of …
intelligence (AI) in diagnostics. This may reduce subjectivity and improve the accuracy of …
Deep learning prediction of steep and flat corneal curvature using fundus photography in post-COVID telemedicine era
JY Choi, H Kim, JK Kim, IS Lee, IH Ryu, JS Kim… - Medical & Biological …, 2024 - Springer
Recently, fundus photography (FP) is being increasingly used. Corneal curvature is an
essential factor in refractive errors and is associated with several pathological corneal …
essential factor in refractive errors and is associated with several pathological corneal …
[HTML][HTML] EnsembleDL-ATG: Identifying autophagy proteins by integrating their sequence and evolutionary information using an ensemble deep learning framework
L Yu, Y Zhang, L Xue, F Liu, R Jing, J Luo - Computational and Structural …, 2023 - Elsevier
Autophagy is a primary mechanism for maintaining cellular homeostasis. The synergistic
actions of autophagy-related (ATG) proteins strictly regulate the whole autophagic process …
actions of autophagy-related (ATG) proteins strictly regulate the whole autophagic process …
DRANetSplicer: A Splice Site Prediction Model Based on Deep Residual Attention Networks
X Liu, H Zhang, Y Zeng, X Zhu, L Zhu, J Fu - Genes, 2024 - mdpi.com
The precise identification of splice sites is essential for unraveling the structure and function
of genes, constituting a pivotal step in the gene annotation process. In this study, we …
of genes, constituting a pivotal step in the gene annotation process. In this study, we …
AdvanceSplice: Integrating N-gram one-hot encoding and ensemble modeling for enhanced accuracy
Accurate splice site prediction is a critical challenge in genomics, essential for
understanding gene expression and disease-associated mutations. Splice sites mark the …
understanding gene expression and disease-associated mutations. Splice sites mark the …
AtLASS: A Scheme for End-to-End Prediction of Splice Sites Using Attention-based Bi-LSTM
R Harada, K Kume, K Horie, T Nakayama… - IPSJ Transactions on …, 2023 - jstage.jst.go.jp
Eukaryotic genomes contain exons and introns, and it is necessary to accurately identify
exon-intron boundaries, ie, splice sites, to annotate genomes. To address this problem …
exon-intron boundaries, ie, splice sites, to annotate genomes. To address this problem …
Sequential labelling and DNABERT For splice site prediction in Homo Sapiens DNA
MA Leksono, A Purwarianti - arXiv preprint arXiv:2212.07638, 2022 - arxiv.org
Genome sequencing technology has improved significantly in few last years and resulted in
abundance genetic data. Artificial intelligence has been employed to analyze genetic data in …
abundance genetic data. Artificial intelligence has been employed to analyze genetic data in …
Splicescanner: An accurate and interpretable deep learning-based method for splice site prediction
R Wang, J Xu, X Huang, W Qi, Y Zhang - International Conference on …, 2023 - Springer
The identification of splice sites is significant to the delineation of gene structure and the
understanding of complicated alternative mechanisms underlying gene transcriptional …
understanding of complicated alternative mechanisms underlying gene transcriptional …
Splam: a deep-learning-based splice site predictor that improves spliced alignments
The process of splicing messenger RNA to remove introns plays a central role in creating
genes and gene variants. We describe Splam, a novel method for predicting splice junctions …
genes and gene variants. We describe Splam, a novel method for predicting splice junctions …
Impact of U2-type introns on splice site prediction in Arabidopsis thaliana using deep learning
In this study, we investigate the impact of introns on the effectiveness of splice site prediction
using deep learning models, focusing on Arabidopsis thaliana. We specifically utilize U2 …
using deep learning models, focusing on Arabidopsis thaliana. We specifically utilize U2 …