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3D full-dose brain-PET volume recovery from low-dose data through deep learning: quantitative assessment and clinical evaluation.
European radiology
Nov 28, 2024
OBJECTIVES: Low-dose (LD) PET imaging would lead to reduced image quality and diagnostic efficacy. We propose a deep learning (DL) method to reduce radiotracer dosage for PET studies while maintaining diagnostic quality.
Pharmacists' perceptions of artificial intelligence: A national survey.
Journal of the American Pharmacists Association : JAPhA
Nov 28, 2024
BACKGROUND: Artificial intelligence (AI) is a rapidly growing and evolving field impacting pharmacy research, education, and professional practice. The development and adaptation of AI technologies have the potential to radically shape the future of ...
Developing predictive models for residual back pain after percutaneous vertebral augmentation treatment for osteoporotic thoracolumbar compression fractures based on machine learning technique.
Journal of orthopaedic surgery and research
Nov 28, 2024
BACKGROUND: Machine learning (ML) has been widely applied to predict the outcomes of numerous diseases. The current study aimed to develop a prognostic prediction model using machine learning algorithms and identify risk factors associated with resid...
Machine learning-based diagnostic model for stroke in non-neurological intensive care unit patients with acute neurological manifestations.
Scientific reports
Nov 28, 2024
Stroke is a neurological complication that can occur in patients admitted to the intensive care unit (ICU) for non-neurological conditions, leading to increased mortality and prolonged hospital stays. The incidence of stroke in ICU settings is notabl...
Cell quantification at the osteochondral interface from synchrotron radiation phase contrast micro-computed tomography images using a deep learning approach.
Scientific reports
Nov 28, 2024
Osteochondral interface consists of two tissues: the calcified cartilage (CC) containing chondrocytes, and subchondral bone (SCB) containing osteocytes that interact with each other. In this study, we propose a new method for the three-dimensional (3...
Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques.
Scientific reports
Nov 28, 2024
Hepatocellular carcinoma (HCC) represents a significant health burden in Egypt, largely attributable to the endemic prevalence of hepatitis B and C viruses. Early identification of HCC remains a challenge due to the lack of widespread screening among...
A deep learning approach for automated scoring of the Rey-Osterrieth complex figure.
eLife
Nov 28, 2024
Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey-Osterrieth complex figure (ROCF) is the state-of-the-art assessment tool for neuropsychologists across the globe to assess the degree of non-verbal visu...
External validation and performance analysis of a deep learning-based model for the detection of intracranial hemorrhage.
The neuroradiology journal
Nov 27, 2024
PurposeWe aimed to investigate the external validation and performance of an FDA-approved deep learning model in labeling intracranial hemorrhage (ICH) cases on a real-world heterogeneous clinical dataset. Furthermore, we delved deeper into evaluatin...
MRI classification and discrimination of spinal schwannoma and meningioma based on deep learning.
Journal of X-ray science and technology
Nov 27, 2024
BACKGROUD: Schwannoma (SCH) and meningiomas (MEN) are the two most common primary spinal cord tumors. Differentiating between them preoperatively remains a clinical challenge due to the substantial overlap in their clinical presentation and imaging c...
Clinical feasibility of a deep learning approach for conventional and synthetic diffusion-weighted imaging in breast cancer: Qualitative and quantitative analyses.
European journal of radiology
Nov 27, 2024
PURPOSE: In this study, we aimed to investigate the clinical feasibility of deep learning (DL)-based reconstruction applied to conventional diffusion-weighted imaging (cDWI) and synthetic diffusion-weighted imaging (sDWI) by comparing the DL reconstr...
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