AI Medical Compendium Topic

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Diagnosis, Differential

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Clinical use of machine learning-based pathomics signature for diagnosis and survival prediction of bladder cancer.

Cancer science
Traditional histopathology performed by pathologists by the naked eye is insufficient for accurate and efficient diagnosis of bladder cancer (BCa). We collected 643 H&E-stained BCa images from Shanghai General Hospital and The Cancer Genome Atlas (TC...

White matter hyperintensities segmentation using the ensemble U-Net with multi-scale highlighting foregrounds.

NeuroImage
White matter hyperintensities (WMHs) are abnormal signals within the white matter region on the human brain MRI and have been associated with aging processes, cognitive decline, and dementia. In the current study, we proposed a U-Net with multi-scale...

Convolutional Sparse Support Estimator-Based COVID-19 Recognition From X-Ray Images.

IEEE transactions on neural networks and learning systems
Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. Deep learning techniques can...

Distinguishing retinal angiomatous proliferation from polypoidal choroidal vasculopathy with a deep neural network based on optical coherence tomography.

Scientific reports
This cross-sectional study aimed to build a deep learning model for detecting neovascular age-related macular degeneration (AMD) and to distinguish retinal angiomatous proliferation (RAP) from polypoidal choroidal vasculopathy (PCV) using a convoluti...

Distinguishing Rectal Cancer from Colon Cancer Based on the Support Vector Machine Method and RNA-sequencing Data.

Current medical science
Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Several studies have indicated that rectal cancer is significantly different from colon cancer in terms of treatment, prognosis, and metastasis. Recently, the differential...

A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.

Nature biomedical engineering
Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneu...

Machine learning-based decision tree classifier for the diagnosis of progressive supranuclear palsy and corticobasal degeneration.

Neuropathology and applied neurobiology
AIMS: This study aimed to clarify the different topographical distribution of tau pathology between progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) and establish a machine learning-based decision tree classifier.

Application of artificial intelligence using a convolutional neural network for detecting cholesteatoma in endoscopic enhanced images.

Auris, nasus, larynx
OBJECTIVE: We examined whether artificial intelligence (AI) used with the novel digital image enhancement system modalities (CLARA+CHROMA, SPECTRA A, and SPECTRA B) could distinguish the cholesteatoma matrix, cholesteatoma debris, and normal middle e...