AIMC Topic: Deep Learning

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Online music-assisted rehabilitation system for depressed people based on deep learning.

Progress in neuro-psychopharmacology & biological psychiatry
The processing of negative emotions is closely related to the occurrence of depression, and improving the mood of patients with depression has an important effect on improving symptoms. This article applies deep learning to the diagnosis and treatmen...

Deep learning methods for enhancing cone-beam CT image quality toward adaptive radiation therapy: A systematic review.

Medical physics
The use of deep learning (DL) to improve cone-beam CT (CBCT) image quality has gained popularity as computational resources and algorithmic sophistication have advanced in tandem. CBCT imaging has the potential to facilitate online adaptive radiation...

Monocular Depth Estimation Using Deep Learning: A Review.

Sensors (Basel, Switzerland)
In current decades, significant advancements in robotics engineering and autonomous vehicles have improved the requirement for precise depth measurements. Depth estimation (DE) is a traditional task in computer vision that can be appropriately predic...

Using Deep Learning with Thermal Imaging for Human Detection in Heavy Smoke Scenarios.

Sensors (Basel, Switzerland)
In this study, we propose using a thermal imaging camera (TIC) with a deep learning model as an intelligent human detection approach during emergency evacuations in a low-visibility smoky fire scenarios. We use low-wavelength infrared (LWIR) images t...

Comparative analysis of high- and low-level deep learning approaches in microsatellite instability prediction.

Scientific reports
Deep learning-based approaches in histopathology can be largely divided into two categories: a high-level approach using an end-to-end model and a low-level approach using feature extractors. Although the advantages and disadvantages of both approach...

Deep learning for automatic brain tumour segmentation on MRI: evaluation of recommended reporting criteria via a reproduction and replication study.

BMJ open
OBJECTIVES: To determine the reproducibility and replicability of studies that develop and validate segmentation methods for brain tumours on MRI and that follow established reproducibility criteria; and to evaluate whether the reporting guidelines a...

Diagnostic Accuracy of Deep Learning and Radiomics in Lung Cancer Staging: A Systematic Review and Meta-Analysis.

Frontiers in public health
BACKGROUND: Artificial intelligence has far surpassed previous related technologies in image recognition and is increasingly used in medical image analysis. We aimed to explore the diagnostic accuracy of the models based on deep learning or radiomics...

Identification of early invisible acute ischemic stroke in non-contrast computed tomography using two-stage deep-learning model.

Theranostics
Although non-contrast computed tomography (NCCT) is the recommended examination for the suspected acute ischemic stroke (AIS), it cannot detect significant changes in the early infarction. We aimed to develop a deep-learning model to identify early ...

Prediction Model of Piano Collective Class Teaching and Learning Effect Based on Deep Learning.

Computational intelligence and neuroscience
This paper proposes a prediction model of piano collective class teaching and learning effect based on DL network in order to realise the precise prediction and evaluation of piano collective class instructional effect and promote the improvement of ...

Deep-Learning-Based Financial Message Sentiment Classification in Business Management.

Computational intelligence and neuroscience
A deep-learning-based financial text sentiment classification method is proposed in this paper, which can provide a reference for business management. In the proposed method, domain adaptation is adopted to solve the common problem of insufficient la...