AIMC Topic: Deep Learning

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Automated cell annotation and classification on histopathology for spatial biomarker discovery.

Nature communications
Histopathology with hematoxylin and eosin (H&E) staining is routinely employed for clinical diagnoses. Single-cell analysis of histopathology provides a powerful tool for understanding the intricate cellular interactions underlying disease progressio...

Vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation.

PloS one
This article proposes a novel approach for vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation named MixNet. In industrial environments where equipment reliability directly im...

Air-ground collaborative multi-source orbital integrated detection system: Combining 3D imaging and intrusion recognition.

PloS one
With the rapid expansion of railway networks globally, ensuring rail infrastructure safety through efficient detection methods has become critical. Traditional inspection systems face limitations in flexibility, adaptability to adverse weather, and m...

Saliency-enhanced infrared and visible image fusion via sub-window variance filter and weighted least squares optimization.

PloS one
This paper proposes a novel method for infrared and visible image fusion (IVIF) to address the limitations of existing techniques in enhancing salient features and improving visual clarity. The method employs a sub-window variance filter (SVF) based ...

Video swin-CLSTM transformer: Enhancing human action recognition with optical flow and long-term dependencies.

PloS one
As video data volumes soar exponentially, the significance of video content analysis, particularly Human Action Recognition (HAR), has become increasingly prominent in fields such as intelligent surveillance, sports analytics, medical rehabilitation,...

Automated facial nerve identification in microsurgery with an improved unet.

Journal of robotic surgery
To develop a deep-learning model that improves the segmentation and detection of Facial Nerve in microsurgery, thereby increasing surgical precision and safety. We collected videos from 25 patients undergoing facial nerve decompression microsurgery. ...

Deep learning-derived optimal annotation strategies to power the systematic mapping of peptide space.

Food chemistry
Rapid and reliable peptide identification techniques are essential for proteomics. High-resolution tandem mass spectrometry acquires a large amount of data through data-dependent acquisition (DDA) and data-independent acquisition (DIA), but tradition...

A deep learning model for preoperative risk stratification of pancreatic ductal adenocarcinoma based on genomic predictors of liver metastasis.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) frequently presents with occult metastatic disease which can undermine the benefit of local treatment. Improved preoperative tools may enhance risk stratification.

Diff-SE: A Diffusion-Augmented Contrastive Learning Framework for Super-Enhancer Prediction.

Journal of chemical information and modeling
Super-enhancers (SEs) are cis-regulatory elements that play crucial roles in gene expression and are implicated in diseases such as cancer and Alzheimer's. Traditional identification methods rely on ChIP-seq experiments, which are costly and time-con...

Ultrahigh-Throughput Virtual Screening Strategies against PPI Targets: A Case Study of STAT Inhibitors.

Journal of chemical information and modeling
In recent years, virtual screening of ultralarge (10) libraries of synthetically accessible compounds (uHTVS) became a popular approach in hit identification. With AI-assisted virtual screening workflows, such as Deep Docking, these protocols might b...