AIMC Topic: Deep Learning

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CREATE: cell-type-specific cis-regulatory element identification via discrete embedding.

Nature communications
Cis-regulatory elements (CREs), including enhancers, silencers, promoters and insulators, play pivotal roles in orchestrating gene regulatory mechanisms that drive complex biological traits. However, current approaches for CRE identification are pred...

Assessing fetal lung maturity: Integration of ultrasound radiomics and deep learning.

African journal of reproductive health
This study built a model to forecast the maturity of lungs by blending radiomics and deep learning methods. We examined ultrasound images from 263 pregnancies in the pregnancy stages. Utilizing the GE VOLUSON E8 system we captured images to extract a...

Deep learning health space model for ordered responses.

BMC medical informatics and decision making
BACKGROUND: As personalized medicine becomes more prevalent, the objective measurement and visualization of an individual's health status are becoming increasingly crucial. However, as the dimensions of data collected from each individual increase, t...

Potato plant disease detection: leveraging hybrid deep learning models.

BMC plant biology
Agriculture, a crucial sector for global economic development and sustainable food production, faces significant challenges in detecting and managing crop diseases. These diseases can greatly impact yield and productivity, making early and accurate d...

Enhanced effective convolutional attention network with squeeze-and-excitation inception module for multi-label clinical document classification.

Scientific reports
Clinical Document Classification (CDC) is crucial in healthcare for organizing and categorizing large volumes of medical information, leading to improved patient care, streamlined research, and enhanced administrative efficiency. With the advancement...

Multicenter development of a deep learning radiomics and dosiomics nomogram to predict radiation pneumonia risk in non-small cell lung cancer.

Scientific reports
Radiation pneumonia (RP) is the most common side effect of chest radiotherapy, and can affect patients' quality of life. This study aimed to establish a combined model of radiomics, dosiomics, deep learning (DL) based on simulated location CT and dos...

The application of suitable sports games for junior high school students based on deep learning and artificial intelligence.

Scientific reports
In the contemporary educational environment, junior high school students' physical education is facing the challenge of improving teaching quality, strengthening students' physique, and cultivating lifelong physical habits. Traditional physical educa...

Deep learning progressive distill for predicting clinical response to conversion therapy from preoperative CT images of advanced gastric cancer patients.

Scientific reports
Identifying patients suitable for conversion therapy through early non-invasive screening is crucial for tailoring treatment in advanced gastric cancer (AGC). This study aimed to develop and validate a deep learning method, utilizing preoperative com...

Exploiting network optimization stability for enhanced PET image denoising using deep image prior.

Physics in medicine and biology
. Positron emission tomography (PET) is affected by statistical noise due to constraints on tracer dose and scan duration, impacting both diagnostic performance and quantitative accuracy. While deep learning-based PET denoising methods have been used...

Patient-specific uncertainty calibration of deep learning-based autosegmentation networks for adaptive MRI-guided lung radiotherapy.

Physics in medicine and biology
Uncertainty assessment of deep learning autosegmentation (DLAS) models can support contour corrections in adaptive radiotherapy (ART), e.g. by utilizing Monte Carlo Dropout (MCD) uncertainty maps. However, poorly calibrated uncertainties at the patie...