AIMC Journal:
Scientific reports
Showing 2141 to 2150 of 6015 articles
Prediction of viral oncoproteins through the combination of generative adversarial networks and machine learning techniques.
Scientific reports
Nov 7, 2024
Viral oncoproteins play crucial roles in transforming normal cells into cancer cells, representing a significant factor in the etiology of various cancers. Traditionally, identifying these oncoproteins is both time-consuming and costly. With advancem...
Artificial intelligence correctly classifies developmental stages of monarch caterpillars enabling better conservation through the use of community science photographs.
Scientific reports
Nov 7, 2024
Rapid technological advances and growing participation from amateur naturalists have made countless images of insects in their natural habitats available on global web portals. Despite advances in automated species identification, traits like develop...
Cross-instrument optical coherence tomography-angiography (OCTA)-based prediction of age-related macular degeneration (AMD) disease activity using artificial intelligence.
Scientific reports
Nov 7, 2024
This study investigates the efficacy of predicting age-related macular degeneration (AMD) activity through deep neural networks (DNN) using a cross-instrument training dataset composed of Optical coherence tomography-angiography (OCTA) images from tw...
Edge computing-based ensemble learning model for health care decision systems.
Scientific reports
Nov 6, 2024
A growing number of humans have suffered severe chronic illnesses, which has caused a boost in the requirement for diagnostic and medical treatment procedures that are both accurate and fast. Improved patient conditions and enhanced Decision-Making S...
Random survival forest algorithm for risk stratification and survival prediction in gastric neuroendocrine neoplasms.
Scientific reports
Nov 6, 2024
This study aimed to construct and assess a machine-learning algorithm designed to forecast survival rates and risk stratification for patients with gastric neuroendocrine neoplasms (gNENs) after diagnosis. Data on patients with gNENs were extracted a...
Speech recognition using an english multimodal corpus with integrated image and depth information.
Scientific reports
Nov 6, 2024
Traditional English corpora mainly collect information from a single modality, but lack information from multimodal information, resulting in low quality of corpus information and certain problems with recognition accuracy. To solve the above problem...
Artificial intelligence-assisted magnetic resonance imaging technology in the differential diagnosis and prognosis prediction of endometrial cancer.
Scientific reports
Nov 6, 2024
It aimed to analyze the value of deep learning algorithm combined with magnetic resonance imaging (MRI) in the risk diagnosis and prognosis of endometrial cancer (EC). Based on the deep learning convolutional neural network (CNN) architecture residua...
Predictive modeling of COVID-19 mortality risk in chronic kidney disease patients using multiple machine learning algorithms.
Scientific reports
Nov 6, 2024
The coronavirus disease 2019 (COVID-19) has a significant impact on the global population, particularly on individuals with chronic kidney disease (CKD). COVID-19 patients with CKD will face a considerably higher risk of mortality than the general po...
Machine learning model for age-related macular degeneration based on heavy metals: The National Health and Nutrition Examination Survey 2005 to 2008.
Scientific reports
Nov 6, 2024
Age-related macular degeneration (AMD) is the leading cause of blindness in older people in developed countries. It has been suggested that heavy metal exposure may be associated with the development of AMD, but most studies have focused on the effec...
Enhanced convolutional neural network architecture optimized by improved chameleon swarm algorithm for melanoma detection using dermatological images.
Scientific reports
Nov 6, 2024
Early detection and treatment of skin cancer are important for patient recovery and survival. Dermoscopy images can help clinicians for timely identification of cancer, but manual diagnosis is time-consuming, costly, and prone to human error. To cond...
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