AIMC Topic: Deep Learning

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Minimizing the effect of white matter lesions on deep learning based tissue segmentation for brain volumetry.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automated methods for segmentation-based brain volumetry may be confounded by the presence of white matter (WM) lesions, which introduce abnormal intensities that can alter the classification of not only neighboring but also distant brain tissue. The...

Deep learning identifies morphological patterns of homologous recombination deficiency in luminal breast cancers from whole slide images.

Cell reports. Medicine
Homologous recombination DNA-repair deficiency (HRD) is becoming a well-recognized marker of platinum salt and polyADP-ribose polymerase inhibitor chemotherapies in ovarian and breast cancers. While large-scale screening for HRD using genomic markers...

Deep Learning in Medical Hyperspectral Images: A Review.

Sensors (Basel, Switzerland)
With the continuous progress of development, deep learning has made good progress in the analysis and recognition of images, which has also triggered some researchers to explore the area of combining deep learning with hyperspectral medical images an...

Depression Detection Based on Hybrid Deep Learning SSCL Framework Using Self-Attention Mechanism: An Application to Social Networking Data.

Sensors (Basel, Switzerland)
In today's world, mental health diseases have become highly prevalent, and depression is one of the mental health problems that has become widespread. According to WHO reports, depression is the second-leading cause of the global burden of diseases. ...

Fast Near-Field Frequency-Diverse Computational Imaging Based on End-to-End Deep-Learning Network.

Sensors (Basel, Switzerland)
The ability to sculpt complex reference waves and probe diverse radiation field patterns have facilitated the rise of metasurface antennas, while there is still a compromise between the required wide operation band and the non-overlapping characteris...

Deep learning based sentiment analysis and offensive language identification on multilingual code-mixed data.

Scientific reports
Sentiment analysis is a process in Natural Language Processing that involves detecting and classifying emotions in texts. The emotion is focused on a specific thing, an object, an incident, or an individual. Although some tasks are concerned with det...

Diagnosis of nasal bone fractures on plain radiographs via convolutional neural networks.

Scientific reports
This study aimed to assess the performance of deep learning (DL) algorithms in the diagnosis of nasal bone fractures on radiographs and compare it with that of experienced radiologists. In this retrospective study, 6713 patients whose nasal radiograp...

A novel knowledge extraction method based on deep learning in fruit domain.

Scientific reports
Knowledge extraction aims to identify entities and extract relations between them from unstructured text, which are in the form of triplets. Analysis of the fruit nutrition domain corpus revealed many overlapping triplets, that is, multiple correspon...

Clustering of single-cell multi-omics data with a multimodal deep learning method.

Nature communications
Single-cell multimodal sequencing technologies are developed to simultaneously profile different modalities of data in the same cell. It provides a unique opportunity to jointly analyze multimodal data at the single-cell level for the identification ...

Detection and localization of hyperfunctioning parathyroid glands on [F]fluorocholine PET/ CT using deep learning - model performance and comparison to human experts.

Radiology and oncology
BACKGROUND: In the setting of primary hyperparathyroidism (PHPT), [F]fluorocholine PET/CT (FCH-PET) has excellent diagnostic performance, with experienced practitioners achieving 97.7% accuracy in localising hyperfunctioning parathyroid tissue (HPTT)...