AIMC Topic: Deep Learning

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Performance of deep learning models in predicting the nugent score to diagnose bacterial vaginosis.

Microbiology spectrum
The Nugent score is a commonly used diagnostic tool for bacterial vaginosis. However, its accuracy depends on the skills of laboratory technicians. This study aimed to evaluate the performance of deep learning models in predicting the Nugent score to...

Blip-up blip-down circular EPI (BUDA-cEPI) for distortion-free dMRI with rapid unrolled deep learning reconstruction.

Magnetic resonance imaging
PURPOSE: BUDA-cEPI has been shown to achieve high-quality, high-resolution diffusion magnetic resonance imaging (dMRI) with fast acquisition time, particularly when used in conjunction with S-LORAKS reconstruction. However, this comes at a cost of mo...

Explainable Deep Learning Approaches for Risk Screening of Periodontitis.

Journal of dental research
Several pieces of evidence have been reported regarding the association between periodontitis and systemic diseases. Despite the emphasized significance of prevention and early diagnosis of periodontitis, there is still a lack of a clinical tool for ...

Advanced framework for multilevel detection of digital video forgeries.

Annals of the New York Academy of Sciences
The rapid expansion of digital media has sparked significant concerns regarding the swift dissemination and potential misuse of forged video content. Existing forgery detection technologies primarily focus on simple forgeries and are still evolving, ...

Deep Learning Recognition of Paroxysmal Kinesigenic Dyskinesia Based on EEG Functional Connectivity.

International journal of neural systems
Paroxysmal kinesigenic dyskinesia (PKD) is a rare neurological disorder marked by transient involuntary movements triggered by sudden actions. Current diagnostic approaches, including genetic screening, face challenges in identifying secondary cases ...

CPIScore: A Deep Learning Approach for Rapid Scoring and Interpretation of Protein-Ligand Binding Interactions.

Journal of chemical information and modeling
Protein-ligand binding affinity prediction is a crucial and challenging task in the field of drug discovery. However, traditional simulation-based computational approaches are often prohibitively time-consuming, limiting their practical utility. In t...

Automated Single Cell Phenotyping of Time-of-Flight Secondary Ion Mass Spectrometry Tissue Images.

Journal of the American Society for Mass Spectrometry
Existing analytical techniques are being improved or applied in new ways to profile the tissue microenvironment (TME) to better understand the role of cells in disease research. Fully understanding the complex interactions between cells of many diffe...

CIS-UNet: Multi-class segmentation of the aorta in computed tomography angiography via context-aware shifted window self-attention.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Advancements in medical imaging and endovascular grafting have facilitated minimally invasive treatments for aortic diseases. Accurate 3D segmentation of the aorta and its branches is crucial for interventions, as inaccurate segmentation can lead to ...

Early multi-cancer detection through deep learning: An anomaly detection approach using Variational Autoencoder.

Journal of biomedical informatics
Cancer is a disease that causes many deaths worldwide. The treatment of cancer is first and foremost a matter of detection, a treatment that is most effective when the disease is detected at an early stage. With the evolution of technology, several c...

DeepKlapred: A deep learning framework for identifying protein lysine lactylation sites via multi-view feature fusion.

International journal of biological macromolecules
Lysine lactylation (Kla) is a post-translational modification (PTM) that holds significant importance in the regulation of various biological processes. While traditional experimental methods are highly accurate for identifying Kla sites, they are bo...