AIMC Topic: Retrospective Studies
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Deep learning for differential diagnosis of parotid tumors based on 2.5D magnetic resonance imaging.
Annals of medicine
Jun 18, 2025
PURPOSE: Accurate preoperative diagnosis of parotid gland tumors (PGTs) is crucial for surgical planning since malignant tumors require more extensive excision. Though fine-needle aspiration biopsy is the diagnostic gold standard, its sensitivity in ...
Multimodal deep learning for predicting unsuccessful recanalization in refractory large vessel occlusion.
European journal of radiology
Jun 18, 2025
PURPOSE: This study explores a multi-modal deep learning approach that integrates pre-intervention neuroimaging and clinical data to predict endovascular therapy (EVT) outcomes in acute ischemic stroke patients. To this end, consecutive stroke patien...
Radiogenomic insights suggest that multiscale tumor heterogeneity is associated with interpretable radiomic features and outcomes in cancer patients.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 18, 2025
BACKGROUND: To develop radiogenomic subtypes and determine the relationships between radiomic phenotypes and multiomics molecular characteristics.
Analysis of maternal fetal outcomes and complete blood count parameters according to the stages of placental abruption: a retrospective study.
European journal of medical research
Jun 18, 2025
BACKGROUND: To compare the demographic characteristics, maternal and perinatal outcomes and hemoglobin parameters according to stages diagnosed with placental abruption.
Machine learning model for predicting recurrence following intensity-modulated radiation therapy in nasopharyngeal carcinoma.
World journal of surgical oncology
Jun 18, 2025
BACKGROUND: Nasopharyngeal carcinoma (NPC) exhibits unique histopathological characteristics compared to other head and neck cancers. The prognosis of NPC patients after intensity-modulated radiation therapy (IMRT) has not been fully studied, and the...
Artificial Intelligence-Based Digital Histologic Classifier for Prostate Cancer Risk Stratification: Independent Blinded Validation in Patients Treated With Radical Prostatectomy.
JCO clinical cancer informatics
Jun 18, 2025
PURPOSE: Artificial intelligence (AI) tools that identify pathologic features from digitized whole-slide images (WSIs) of prostate cancer (CaP) generate data to predict outcomes. The objective of this study was to evaluate the clinical validity of an...
Development and validation of a deep learning-based automatic classification algorithm for the medial temporal lobe atrophy score using a multimodality cascade transformer.
Clinical radiology
Jun 17, 2025
AIM: The aim of this study was to develop and validate a deep learning-based automatic classification algorithm for the medial temporal lobe atrophy (MTA) score in patients with cognitive impairment.
Earlier discharge from pulmonary nodule follow-up using artificial intelligence based volume measurements in computed tomography.
European journal of radiology
Jun 17, 2025
BACKGROUND: Lung cancer is the leading cause of cancer death worldwide. Effective screening and early detection are critical in reducing mortality. Artificial intelligence (AI) methods have been proved useful in the diagnosis of pulmonary nodules and...
Humans
Reproducibility of Results
Aged
Sensitivity and Specificity
Male
Middle Aged
Artificial Intelligence
Retrospective Studies
Tomography, X-Ray Computed
Female
Early Detection of Cancer
Radiographic Image Interpretation, Computer-Assisted
Patient Discharge
Lung Neoplasms
Follow-Up Studies
Multiple Pulmonary Nodules
Solitary Pulmonary Nodule
Impact of Field-of-view Zooming and Segmentation Batches on Radiomics Features Reproducibility and Machine Learning Performance in Thyroid Scintigraphy.
Clinical nuclear medicine
Jun 17, 2025
BACKGROUND: Thyroid diseases are the second most common hormonal disorders, necessitating accurate diagnostics. Advances in artificial intelligence and radiomics have enhanced diagnostic precision by analyzing quantitative imaging features. However, ...
Predicting 14-day readmission in middle-aged and elderly patients with pneumonia using emergency department data: a multicentre retrospective cohort study with a survival machine learning approach.
BMJ open
Jun 17, 2025
OBJECTIVES: Unplanned pneumonia readmissions increase patient morbidity, mortality and healthcare costs. Among pneumonia patients, the middle-aged and elderly (≥45 years old) have a significantly higher risk of readmission compared with the young. Gi...
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