AIMC Journal:
Scientific reports
Showing 1691 to 1700 of 5371 articles
Linking disease activity with optical coherence tomography angiography in neovascular age related macular degeneration using artificial intelligence.
Scientific reports
Aug 20, 2024
To investigate quantitative associations between AI-assessed disease activity and optical coherence tomography angiography (OCTA)-derived parameters in patients with neovascular age-related macular degeneration (nAMD) undergoing anti-VEGF therapy. OC...
A novel approach for automatic classification of macular degeneration OCT images.
Scientific reports
Aug 20, 2024
Age-related macular degeneration (AMD) and diabetic macular edema (DME) are significant causes of blindness worldwide. The prevalence of these diseases is steadily increasing due to population aging. Therefore, early diagnosis and prevention are cruc...
Indirect reference interval estimation using a convolutional neural network with application to cancer antigen 125.
Scientific reports
Aug 20, 2024
Indirect methods for reference interval (RI) estimation, which use data acquired from routine pathology testing, have the potential to accelerate the establishment of RIs to account for variables such as gender and age to improve clinical assessments...
Identification of copper death-associated molecular clusters and immunological profiles for lumbar disc herniation based on the machine learning.
Scientific reports
Aug 20, 2024
Lumbar disc herniation (LDH) is a common clinical spinal disorder, yet its etiology remains unclear. We aimed to explore the role of cuproptosis-related genes (CRGs) and identify potential diagnostic biomarkers. Our analysis involved interrogating th...
Optimizing oocyte yield utilizing a machine learning model for dose and trigger decisions, a multi-center, prospective study.
Scientific reports
Aug 20, 2024
The objective of this study was to evaluate clinical outcomes for patients undergoing IVF treatment where an artificial intelligence (AI) platform was utilized by clinicians to help determine the optimal starting dose of FSH and timing of trigger inj...
Deciphering the role of HLF in idiopathic orbital inflammation: integrative analysis via bioinformatics and machine learning techniques.
Scientific reports
Aug 20, 2024
Idiopathic orbital inflammation, formerly known as NSOI (nonspecific orbital inflammation), is characterized as a spectrum disorder distinguished by the polymorphic infiltration of lymphoid tissue, presenting a complex and poorly understood etiology....
Decoding myasthenia gravis: advanced diagnosis with infrared spectroscopy and machine learning.
Scientific reports
Aug 20, 2024
Myasthenia Gravis (MG) is a rare neurological disease. Although there are intensive efforts, the underlying mechanism of MG still has not been fully elucidated, and early diagnosis is still a question mark. Diagnostic paraclinical tests are also time...
Enhancing COVID-19 forecasting precision through the integration of compartmental models, machine learning and variants.
Scientific reports
Aug 19, 2024
Predicting epidemic evolution is essential for making informed decisions and guiding the implementation of necessary countermeasures. Computational models are vital tools that provide insights into illness progression and enable early detection, proa...
Predicting the risk category of thymoma with machine learning-based computed tomography radiomics signatures and their between-imaging phase differences.
Scientific reports
Aug 19, 2024
The aim of this study was to develop a medical imaging and comprehensive stacked learning-based method for predicting high- and low-risk thymoma. A total of 126 patients with thymomas and 5 patients with thymic carcinoma treated at our institution, i...
An efficient colorectal cancer detection network using atrous convolution with coordinate attention transformer and histopathological images.
Scientific reports
Aug 17, 2024
The second most common type of malignant tumor worldwide is colorectal cancer. Histopathology image analysis offers crucial data for the clinical diagnosis of colorectal cancer. Currently, deep learning techniques are applied to enhance cancer classi...
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