AIMC Topic: Humans

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IDNetwork: A deep illness-death network based on multi-state event history process for disease prognostication.

Statistics in medicine
Multi-state models can capture the different patterns of disease evolution. In particular, the illness-death model is used to follow disease progression from a healthy state to an intermediate state of the disease and to a death-related final state. ...

[The analysis of CIRSmedical.de using Natural Language Processing].

Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen
BACKGROUND: CIRSmedical.de is a publicly accessible, cross-institutional reporting and learning system, which is organized by the German Agency for Quality in Medicine (ÄZQ). CIRSmedical.de has existed since 2005 and has published more than 6,000 eve...

Deep learning-based diagnosis models for onychomycosis in dermoscopy.

Mycoses
BACKGROUND: Onychomycosis is a common disease. Emerging noninvasive, real-time techniques such as dermoscopy and deep convolutional neural networks have been proposed for the diagnosis of onychomycosis. However, deep learning application in dermoscop...

Robot-assisted kidney transplantation as a minimally invasive approach for kidney transplant recipients: A systematic review and meta-analyses.

International journal of surgery (London, England)
BACKGROUND: Robot-assisted kidney transplantation (RAKT) has emerged as an alternative for kidney transplant recipients with the potential benefits of minimally invasive surgery. The aim of this systematic review and meta-analysis is to compare the c...

Assessment and validation of a novel fast fully automated artificial intelligence left ventricular ejection fraction quantification software.

Echocardiography (Mount Kisco, N.Y.)
BACKGROUND: Quantification of left ventricular ejection fraction (LVEF) by transthoracic echocardiography (TTE) is operator-dependent, time-consuming, and error-prone. LVivoEF by DIA is a new artificial intelligence (AI) software, which displays the ...

Automated 3D Fetal Brain Segmentation Using an Optimized Deep Learning Approach.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: MR imaging provides critical information about fetal brain growth and development. Currently, morphologic analysis primarily relies on manual segmentation, which is time-intensive and has limited repeatability. This work aimed...

Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools.

Circulation research
Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on sex- and gender-based differences in cardiovascular disease development and outcomes, the need for more effective approaches to screening for risk fact...

Automatic Colorectal Cancer Screening Using Deep Learning in Spatial Light Interference Microscopy Data.

Cells
The surgical pathology workflow currently adopted by clinics uses staining to reveal tissue architecture within thin sections. A trained pathologist then conducts a visual examination of these slices and, since the investigation is based on an empiri...

Artificial intelligence enabled automated diagnosis and grading of ulcerative colitis endoscopy images.

Scientific reports
Endoscopic evaluation to reliably grade disease activity, detect complications including cancer and verification of mucosal healing are paramount in the care of patients with ulcerative colitis (UC); but this evaluation is hampered by substantial int...

Machine learning classification of schizophrenia patients and healthy controls using diverse neuroanatomical markers and Ensemble methods.

Scientific reports
Schizophrenia is a major psychiatric disorder that imposes enormous clinical burden on patients and their caregivers. Determining classification biomarkers can complement clinical measures and improve understanding of the neural basis underlying schi...