AIMC Topic: Deep Learning

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Coronary heart disease prediction based on hybrid deep learning.

The Review of scientific instruments
Machine learning provides increasingly reliable assistance for medical experts in diagnosing coronary heart disease. This study proposes a deep learning hybrid model based coronary heart disease (CAD) prediction method, which can significantly improv...

Deep learning to extract the meteorological by-catch of wildlife cameras.

Global change biology
Microclimate-proximal climatic variation at scales of metres and minutes-can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature centric, and do not consider meteorological factors ...

The application value of deep learning in the background of precision medicine in glioblastoma.

Science progress
Glioblastoma is a highly malignant central nervous system tumor, World Health Organization Ⅳ, glioblastoma is the most common primary malignancy, due to its own specificity and complexity, different patients often benefit from the current convention...

On phase recovery and preserving early reflections for deep-learning speech dereverberation.

The Journal of the Acoustical Society of America
In indoor environments, reverberation often distorts clean speech. Although deep learning-based speech dereverberation approaches have shown much better performance than traditional ones, the inferior speech quality of the dereverberated speech cause...

Image-Based Subtype Classification for Glioblastoma Using Deep Learning: Prognostic Significance and Biologic Relevance.

JCO clinical cancer informatics
PURPOSE: To apply deep learning algorithms to histopathology images, construct image-based subtypes independent of known clinical and molecular classifications for glioblastoma, and produce novel insights into molecular and immune characteristics of ...

Binary fire hawks optimizer with deep learning driven non-invasive diabetes detection and classification.

Bratislavske lekarske listy
Non-invasive diabetes detection refers to the utilization and development of technologies and methods that can monitor and diagnose diabetes without requiring invasive procedures, namely invasive glucose monitoring or blood sampling. The objective is...

Multimodal feature fusion in deep learning for comprehensive dental condition classification.

Journal of X-ray science and technology
BACKGROUND: Dental health issues are on the rise, necessitating prompt and precise diagnosis. Automated dental condition classification can support this need.

Identification of L5 vertebra on lumbar spine radiographs using deep learning.

The Journal of international medical research
OBJECTIVE: Deep learning is an advanced machine-learning approach that is used in several medical fields. Here, we developed a deep learning model using an object detection algorithm to identify the L5 vertebra on anteroposterior lumbar spine radiogr...