AIMC Topic: Aged

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Generative artificial intelligence enables the generation of bone scintigraphy images and improves generalization of deep learning models in data-constrained environments.

European journal of nuclear medicine and molecular imaging
PURPOSE: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generat...

Triaging mammography with artificial intelligence: an implementation study.

Breast cancer research and treatment
PURPOSE: Many breast centers are unable to provide immediate results at the time of screening mammography which results in delayed patient care. Implementing artificial intelligence (AI) could identify patients who may have breast cancer and accelera...

Ultrasound Predicts Drug-Induced Sleep Endoscopy Findings Using Machine Learning Models.

The Laryngoscope
OBJECTIVES: Ultrasound is a promising low-risk imaging modality that can provide objective airway measurements that may circumvent limitations of drug-induced sleep endoscopy (DISE). This study was devised to identify ultrasound-derived anatomical me...

Deep Learning-Based Precontrast CT Parcellation for MRI-Free Brain Amyloid PET Quantification.

Clinical nuclear medicine
PURPOSE: This study aimed to develop a deep learning (DL) model for brain region parcellation using CT data from PET/CT scans to enable accurate amyloid quantification in 18 F-FBB PET/CT without relying on high-resolution MRI.

Development and external validation of a machine learning model to predict the initial dose of vancomycin for targeting an area under the concentration-time curve of 400-600 mg∙h/L.

International journal of medical informatics
PURPOSE: To develop and validate a novel artificial intelligence model for predicting the initial empiric dose of vancomycin, with the aim of achieving an area under the concentration-time curve (AUC) of 400-600 mg∙h/L, using individual clinical data...

Enhancing quantitative coronary angiography (QCA) with advanced artificial intelligence: comparison with manual QCA and visual estimation.

The international journal of cardiovascular imaging
Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address manual QCA's limitations in reproducibility and correction process. The present study aimed to assess the performance of an updated AI-QCA solution (MP...

Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing.

Parasites & vectors
BACKGROUND: Amebiasis represents a significant global health concern. This is especially evident in developing countries, where infections are more common. The primary diagnostic method in laboratories involves the microscopy of stool samples. Howeve...