AIMC Topic: Deep Learning

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Automated evaluation with deep learning of total interstitial inflammation and peritubular capillaritis on kidney biopsies.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: Interstitial inflammation and peritubular capillaritis are observed in many diseases on native and transplant kidney biopsies. A precise and automated evaluation of these histological criteria could help stratify patients' kidney prognose...

Quantitative level determination of fixed restorations on panoramic radiographs using deep learning.

International journal of computerized dentistry
AIM: Although many studies in various fields employ deep learning models, only a few such studies exist in dental imaging. The present article aims to evaluate the effectiveness of convolutional neural network (CNN) algorithms for the detection and d...

Design and deep learning of synthetic B-cell-specific promoters.

Nucleic acids research
Synthetic biology and deep learning synergistically revolutionize our ability for decoding and recoding DNA regulatory grammar. The B-cell-specific transcriptional regulation is intricate, and unlock the potential of B-cell-specific promoters as synt...

Single-cell dissection, hdWGCNA and deep learning reveal the role of oxidatively stressed plasma cells in ulcerative colitis.

Acta biochimica et biophysica Sinica
Ulcerative colitis (UC) develops as a result of complex interactions between various cell types in the mucosal microenvironment. In this study, we aim to elucidate the pathogenesis of ulcerative colitis at the single-cell level and unveil its clinica...

Colon Disease Classification Method Based on Deep Learning.

Studies in health technology and informatics
Objective Colorectal cancer (CRC) is a common malignant tumor of the digestive system with a high incidence rate. It is prone to misdiagnosis or missed diagnosis in clinical practice. Therefore, researching computer-aided diagnostic methods for endos...

Research on Brain Signals Classification Based on Deep Learning.

Studies in health technology and informatics
With the continuous expansion of brain-computer communication, the precise identification of brain signals has become an essential task for brain-computer equipment. However, existing classification methods are primarily concentrated on the extractio...

Research on Pectoral Muscle Segmentation Algorithm of CT Image Based on Deep Learning.

Studies in health technology and informatics
Chronic obstructive pulmonary disease (COPD) is a common respiratory disease, which seriously endangers human health and is also one of the important causes of death. The death rate of COPD in China is the highest in the world, and the problem of und...

Integrated bulk and single-cell transcriptomes reveal pyroptotic signature in prognosis and therapeutic options of hepatocellular carcinoma by combining deep learning.

Briefings in bioinformatics
Although some pyroptosis-related (PR) prognostic models for cancers have been reported, pyroptosis-based features have not been fully discovered at the single-cell level in hepatocellular carcinoma (HCC). In this study, by deeply integrating single-c...

NanoDeep: a deep learning framework for nanopore adaptive sampling on microbial sequencing.

Briefings in bioinformatics
Nanopore sequencers can enrich or deplete the targeted DNA molecules in a library by reversing the voltage across individual nanopores. However, it requires substantial computational resources to achieve rapid operations in parallel at read-time sequ...

DLTKcat: deep learning-based prediction of temperature-dependent enzyme turnover rates.

Briefings in bioinformatics
The enzyme turnover rate, ${k}_{cat}$, quantifies enzyme kinetics by indicating the maximum efficiency of enzyme catalysis. Despite its importance, ${k}_{cat}$ values remain scarce in databases for most organisms, primarily because of the cost of exp...