AIMC Topic: Case-Control Studies

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Machine Learning-Based MRI LAVA Dynamic Enhanced Scanning for the Diagnosis of Hilar Lesions.

Computational and mathematical methods in medicine
OBJECTIVE: To explore the value of machine learning-based magnetic resonance imaging (MRI) liver acceleration volume acquisition (LAVA) dynamic enhanced scanning for diagnosing hilar lesions.

Machine Learning Identifies Pan-Cancer Landscape of Nrf2 Oxidative Stress Response Pathway-Related Genes.

Oxidative medicine and cellular longevity
BACKGROUND: Oxidative stress produced a large amount of reactive oxygen species (ROS), which played a pivotal role in balanced ability and determining cell fate. The activated Nrf2 signaling pathway that responds to the excessive ROS regulated the ex...

A deep learning algorithm to identify cervical ossification of posterior longitudinal ligaments on radiography.

Scientific reports
The cervical ossification of the posterior longitudinal ligament (cOPLL) is sometimes misdiagnosed or overlooked on radiography. Thus, this study aimed to validate the diagnostic yield of our deep learning algorithm which diagnose the presence/absenc...

Deep learning based diagnosis for cysts and tumors of jaw with massive healthy samples.

Scientific reports
We aimed to develop an explainable and reliable method to diagnose cysts and tumors of the jaw with massive panoramic radiographs of healthy peoples based on deep learning, since collecting and labeling massive lesion samples are time-consuming, and ...

Assessing central serous chorioretinopathy with deep learning and multiple optical coherence tomography images.

Scientific reports
Central serous chorioretinopathy (CSC) is one of the most common macular diseases that can reduce the quality of life of patients. This study aimed to build a deep learning-based classification model using multiple spectral domain optical coherence t...

Account of Deep Learning-Based Ultrasonic Image Feature in the Diagnosis of Severe Sepsis Complicated with Acute Kidney Injury.

Computational and mathematical methods in medicine
This study was aimed at analyzing the diagnostic value of convolutional neural network models on account of deep learning for severe sepsis complicated with acute kidney injury and providing an effective theoretical reference for the clinical use of ...

Evaluation of deep convolutional neural networks for in situ hybridization gene expression image representation.

PloS one
High resolution in situ hybridization (ISH) images of the brain capture spatial gene expression at cellular resolution. These spatial profiles are key to understanding brain organization at the molecular level. Previously, manual qualitative scoring ...

Artificial intelligence deep learning model assessment of leukocyte counts and proliferation in endometrium from women with and without polycystic ovary syndrome.

F&S science
OBJECTIVE: To study whether artificial intelligence (AI) technology can be used to discern quantitative differences in endometrial immune cells between cycle phases and between samples from women with polycystic ovary syndrome (PCOS) and non-PCOS con...

Automated detection of COVID-19 through convolutional neural network using chest x-ray images.

PloS one
The COVID-19 epidemic has a catastrophic impact on global well-being and public health. More than 27 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, and challenges to the variations of the...

Deep Learning-Based Chest CT Image Features in Diagnosis of Lung Cancer.

Computational and mathematical methods in medicine
This study was to evaluate the diagnostic value of deep learning-optimized chest CT in the patients with lung cancer. 90 patients who were diagnosed with lung cancer by surgery or puncture in hospital were selected as the research subjects. The Mask ...