AIMC Journal:
Scientific reports
Showing 981 to 990 of 5361 articles
Assessing the diagnostic accuracy of machine learning algorithms for identification of asthma in United States adults based on NHANES dataset.
Scientific reports
Feb 6, 2025
Asthma diagnosis poses challenges due to underreporting of symptoms, misdiagnoses, and limitations in existing diagnostic tests. Machine learning (ML) offers a promising avenue for addressing these challenges by leveraging demographic and clinical da...
A deep ensemble learning framework for glioma segmentation and grading prediction.
Scientific reports
Feb 6, 2025
The segmentation and risk grade prediction of gliomas based on preoperative multimodal magnetic resonance imaging (MRI) are crucial tasks in computer-aided diagnosis. Due to the significant heterogeneity between and within tumors, existing methods ma...
Artificial intelligence-driven ensemble deep learning models for smart monitoring of indoor activities in IoT environment for people with disabilities.
Scientific reports
Feb 5, 2025
Disabled persons demanding healthcare is a developing global occurrence. The support in longer-term care includes nursing, intricate medical, recovery, and social help services. The price is large, but advanced technologies can aid in decreasing expe...
Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection.
Scientific reports
Feb 5, 2025
Employing two standard mammography views is crucial for radiologists, providing comprehensive insights for reliable clinical evaluations. This study introduces paired mammogram view based-network(PMVnet), a novel algorithm designed to enhance breast ...
Machine learning for classifying chronic kidney disease and predicting creatinine levels using at-home measurements.
Scientific reports
Feb 5, 2025
Chronic kidney disease (CKD) is a global health concern with early detection playing a pivotal role in effective management. Machine learning models demonstrate promise in CKD detection, yet the impact on detection and classification using different ...
Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values.
Scientific reports
Feb 5, 2025
This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to predict systemic inflammatory response syndrome (SIRS) after endoscopic surgery for kidney stones. The goal is to identify high-risk patients early and p...
Breast cancer classification based on hybrid CNN with LSTM model.
Scientific reports
Feb 5, 2025
Breast cancer (BC) is a global problem, largely due to a shortage of knowledge and early detection. The speed-up process of detection and classification is crucial for effective cancer treatment. Medical image analysis methods and computer-aided diag...
Optimizing chickpea yield prediction under wilt disease through synergistic integration of biophysical and image parameters using machine learning models.
Scientific reports
Feb 5, 2025
Crop health assessment and early yield predictions are highly crucial under biotic stress conditions for crop management and market planning by farmers and policy planners. The objective of this study was, therefore, to assess the impact of different...
Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer.
Scientific reports
Feb 4, 2025
Gastric cancer (GC) is one of the most common tumors; one of the reasons for its poor prognosis is that GC cells can resist normal cell death process and therefore develop distant metastasis. Cuproptosis is a novel type of cell death and a limited nu...
A novel aggregated coefficient ranking based feature selection strategy for enhancing the diagnosis of breast cancer classification using machine learning.
Scientific reports
Feb 4, 2025
Effective Breast cancer (BC) analysis is crucial for early prognosis, controlling cancer recurrence, timely medical intervention, and determining appropriate treatment procedures. Additionally, it plays a significant role in optimizing mortality rate...
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