AIMC Topic: Deep Learning

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scRSSL: Residual semi-supervised learning with deep generative models to automatically identify cell types.

IET systems biology
Single-cell sequencing (scRNA-seq) allows researchers to study cellular heterogeneity in individual cells. In single-cell transcriptomics analysis, identifying the cell type of individual cells is a key task. At present, single-cell datasets often fa...

A Multimodal Approach for Early Identification of Mild Cognitive Impairment and Alzheimer's Disease With Fusion Network Using Eye Movements and Speech.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Detecting Alzheimer's disease (AD) in its earliest stages, particularly during an onset of Mild Cognitive Impairment (MCI), remains challenging due to the overlap of initial symptoms with normal aging processes. Given that no cure exists and current ...

Enhancing forensic shoeprint analysis: Application of the Shoe-MS algorithm to challenging evidence.

Science & justice : journal of the Forensic Science Society
Quantitative assessment of pattern evidence is a challenging task, particularly in the context of forensic investigations where the accurate identification of sources and classification of items in evidence are critical. Emerging deep learning approa...

Causal recurrent intervention for cross-modal cardiac image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Cross-modal cardiac image segmentation is essential for cardiac disease analysis. In diagnosis, it enables clinicians to obtain more precise information about cardiac structure or function for potential signs by leveraging specific imaging modalities...

OrgaMeas: A pipeline that integrates all the processes of organelle image analysis.

Biochimica et biophysica acta. Molecular cell research
Although image analysis has emerged as a key technology in the study of organelle dynamics, the commonly used image-processing methods, such as threshold-based segmentation and manual setting of regions of interests (ROIs), are error-prone and labori...

Early operative difficulty assessment in laparoscopic cholecystectomy via snapshot-centric video analysis.

International journal of computer assisted radiology and surgery
PURPOSE: Laparoscopic cholecystectomy (LC) operative difficulty (LCOD) is highly variable and influences outcomes. Despite extensive LC studies in surgical workflow analysis, limited efforts explore LCOD using intraoperative video data. Early recogni...

Towards real-time conformal palliative treatment of spine metastases: A deep learning approach for Hounsfield Unit recovery of cone beam CT images.

Medical physics
BACKGROUND: The extension of onboard cone-beam CT (CBCT) imaging for real-time treatment planning is constrained by limitations in image quality. Synthetic CT (sCT) generation using deep learning provides a potential solution to these limitations.

A CVAE-based generative model for generalized B inhomogeneity corrected chemical exchange saturation transfer MRI at 5 T.

NeuroImage
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a powerful tool to image endogenous or exogenous macromolecules. CEST contrast highly depends on radiofrequency irradiation B level. Spatial inhomogeneity of...

The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning.

International journal of biological macromolecules
Biological interactions between RNA and small-molecule ligands play a crucial role in determining the specific functions of RNA, such as catalysis and folding, and are essential for guiding drug design in the medical field. Accurately predicting the ...

Combining Ultrasound Imaging and Molecular Testing in a Multimodal Deep Learning Model for Risk Stratification of Indeterminate Thyroid Nodules.

Thyroid : official journal of the American Thyroid Association
Indeterminate cytology (Bethesda III and IV) represents 15-30% of biopsied thyroid nodules and require additional diagnostic testing. Molecular testing (MT) is a commonly used diagnostic tool that evaluatesmalignancy risk through next generation seq...