AIMC Topic: ROC Curve
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CT-Based Machine Learning Radiomics Analysis to Diagnose Dysthyroid Optic Neuropathy.
Seminars in ophthalmology
Feb 19, 2025
PURPOSE: To develop CT-based machine learning radiomics models used for the diagnosis of dysthyroid optic neuropathy (DON).
Electrocardiographic-Driven artificial intelligence Model: A new approach to predicting One-Year mortality in heart failure with reduced ejection fraction patients.
International journal of medical informatics
Feb 19, 2025
BACKGROUND: Despite the proliferation of heart failure (HF) mortality prediction models, their practical utility is limited. Addressing this, we utilized a significant dataset to develop and validate a deep learning artificial intelligence (AI) model...
Integrating ultrasound radiomics and clinicopathological features for machine learning-based survival prediction in patients with nonmetastatic triple-negative breast cancer.
BMC cancer
Feb 18, 2025
OBJECTIVE: This study aimed to evaluate the predictive value of implementing machine learning models based on ultrasound radiomics and clinicopathological features in the survival analysis of triple-negative breast cancer (TNBC) patients.
Development and validation of interpretable machine learning models for triage patients admitted to the intensive care unit.
PloS one
Feb 18, 2025
OBJECTIVES: Developing and validating interpretable machine learning (ML) models for predicting whether triaged patients need to be admitted to the intensive care unit (ICU).
Supervised machine learning compared to large language models for identifying functional seizures from medical records.
Epilepsia
Feb 17, 2025
OBJECTIVE: The Functional Seizures Likelihood Score (FSLS) is a supervised machine learning-based diagnostic score that was developed to differentiate functional seizures (FS) from epileptic seizures (ES). In contrast to this targeted approach, large...
A predictive model for recurrence in patients with borderline ovarian tumor based on neural multi-task logistic regression.
BMC cancer
Feb 17, 2025
BACKGROUND: Effective management of patients with borderline ovarian tumor (BOT) requires the timely identification of those at a higher risk of recurrence. Artificial neural networks have been successfully used in many areas of clinical event predic...
Prediction of tuberculosis treatment outcomes using biochemical makers with machine learning.
BMC infectious diseases
Feb 17, 2025
BACKGROUND: Tuberculosis (TB) continues to pose a significant threat to global public health. Enhancing patient prognosis is essential for alleviating the disease burden.
Dense convolution-based attention network for Alzheimer's disease classification.
Scientific reports
Feb 17, 2025
Recently, deep learning-based medical image classification models have made substantial advancements. However, many existing models prioritize performance at the cost of efficiency, limiting their practicality in clinical use. Traditional Convolution...
Artificial intelligence can extract important features for diagnosing axillary lymph node metastasis in early breast cancer using contrast-enhanced ultrasonography.
Scientific reports
Feb 15, 2025
Contrast-enhanced ultrasound (CEUS) plays a pivotal role in the diagnosis of primary breast cancer and in axillary lymph node (ALN) metastasis. However, the imaging features that are clinically crucial for lymph node metastasis have not been fully el...
Deep learning for detecting and early predicting chronic obstructive pulmonary disease from spirogram time series.
NPJ systems biology and applications
Feb 15, 2025
Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung condition characterized by airflow obstruction. Current diagnostic methods primarily rely on identifying prominent features in spirometry (Volume-Flow time series) to detect COPD, but the...
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