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PSMA PET/CT based multimodal deep learning model for accurate prediction of pelvic lymph-node metastases in prostate cancer patients identified as candidates for extended pelvic lymph node dissection by preoperative nomograms.
European journal of nuclear medicine and molecular imaging
Jan 27, 2025
PURPOSE: To develop and validate a prostate-specific membrane antigen (PSMA) PET/CT based multimodal deep learning model for predicting pathological lymph node invasion (LNI) in prostate cancer (PCa) patients identified as candidates for extended pel...
Non-experimental rapid identification of lower respiratory tract infections in patients with chronic obstructive pulmonary disease using multi-label learning.
Computer methods and programs in biomedicine
Jan 27, 2025
BACKGROUND AND OBJECTIVE: Microbiological culture is a standard diagnostic test that takes a long time to identify lower respiratory tract infections (LRTI) in patients with chronic obstructive pulmonary disease (COPD). This study entailed the develo...
A deep-learning system integrating electrocardiograms and laboratory indicators for diagnosing acute aortic dissection and acute myocardial infarction.
International journal of cardiology
Jan 27, 2025
BACKGROUND: Acute Stanford Type A aortic dissection (AAD-type A) and acute myocardial infarction (AMI) present with similar symptoms but require distinct treatments. Efficient differentiation is critical due to limited access to radiological equipmen...
Automatic segmentation and volumetric analysis of intracranial hemorrhages in brain CT images.
European journal of radiology
Jan 27, 2025
BACKGROUND: Intracranial hemorrhages (ICH) are life-threatening conditions that require rapid detection and precise subtype classification. Automated segmentation and volumetric analysis using deep learning can enhance clinical decision-making.
A multi-model machine learning framework for breast cancer risk stratification using clinical and imaging data.
Journal of X-ray science and technology
Jan 27, 2025
PurposeThis study presents a comprehensive machine learning framework for assessing breast cancer malignancy by integrating clinical features with imaging features derived from deep learning.MethodsThe dataset included 1668 patients with documented b...
Detecting IDH and TERTp mutations in diffuse gliomas using H-MRS with attention deep-shallow networks.
Computers in biology and medicine
Jan 27, 2025
BACKGROUND: Preoperative and noninvasive detection of isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) mutations in glioma is critical for prognosis and treatment planning. This study aims to develop deep lear...
Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis.
Computers in biology and medicine
Jan 27, 2025
An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. The study involved thirty-three l...
Significance of gender, brain region and EEG band complexity analysis for Parkinson's disease classification using recurrence plots and machine learning algorithms.
Physical and engineering sciences in medicine
Jan 27, 2025
Parkinson Disease (PD) is a complex neurological disorder attributed by loss of neurons generating dopamine in the SN per compacta. Electroencephalogram (EEG) plays an important role in diagnosing PD as it offers a non-invasive continuous assessment ...
Development and Validation of Machine Learning-Based Model for Hospital Length of Stay in Patients Undergoing Endovascular Interventional Embolization for Intracranial Aneurysms.
World neurosurgery
Jan 27, 2025
OBJECTIVE: This study was to explore the factors associated with prolonged hospital length of stay (LOS) in patients with intracranial aneurysms (IAs) undergoing endovascular interventional embolization and construct prediction model machine learning...
Optimizing stroke prediction using gated recurrent unit and feature selection in Sub-Saharan Africa.
Clinical neurology and neurosurgery
Jan 27, 2025
BACKGROUND: Stroke remains a leading cause of death and disability worldwide, with African populations bearing a disproportionately high burden due to limited healthcare infrastructure. Early prediction and intervention are critical to reducing strok...
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