IEEE journal of biomedical and health informatics
Nov 11, 2022
Precise and quick monitoring of key cytometric features such as cell count, size, morphology, and DNA content is crucial in life science applications. Traditionally, image cytometry relies on visual inspection of hemocytometers. This approach is erro...
Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
Nov 10, 2022
BACKGROUND: Line-field confocal optical coherence tomography (LC-OCT) is an imaging technique providing non-invasive "optical biopsies" with an isotropic spatial resolution of ∼1 μm and deep penetration until the dermis. Analysis of obtained images ...
To evaluate and establish a prediction model of the outcome of induced labor based on machine learning algorithm. This was a cross-sectional design. The subjects were divided into primipara and multipara, and the risk factors for the outcomes of indu...
This study compares a deep learning interpretation of 23 echocardiographic parameters-including cardiac volumes, ejection fraction, and Doppler measurements-with three repeated measurements by core lab sonographers. The primary outcome metric, the in...
BACKGROUND: According to the WHO, anemia is a highly prevalent disease, especially for patients in the emergency department. The pathophysiological mechanism by which anemia can affect facial characteristics, such as membrane pallor, has been proven ...
Programmed death ligand-1 (PD-L1) has been recently adopted for breast cancer as a predictive biomarker for immunotherapies. The cost, time, and variability of PD-L1 quantification by immunohistochemistry (IHC) are a challenge. In contrast, hematoxyl...
Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
Nov 7, 2022
PURPOSE: Outcome prediction of large vessel occlusion of the anterior circulation in patients with wake-up stroke is important to identify patients that will benefit from thrombectomy. Currently, mismatch concepts that require MRI or CT-Perfusion (CT...
The purpose of this study was to develop a deep learning model to diagnose breast cancer by embedding a diagnostic algorithm that examines the asymmetry of bilateral breast tissue. This retrospective study was approved by the institutional review boa...
BACKGROUND: This paper attempts to conduct a systematic review and meta-analysis of deep learning (DLs) models for cervical cancer CT image segmentation.
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