AIMC Topic: Humans

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A comparison of two artificial intelligence-based methods for assessing bone age in Turkish children: BoneXpert and VUNO Med-Bone Age.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: This study aimed to evaluate the validity of two artificial intelligence (AI)-based bone age assessment programs, BoneXpert and VUNO Med-Bone Age (VUNO), compared with manual assessments using the Greulich-Pyle method in Turkish children.

A retrospective evaluation of the potential of ChatGPT in the accurate diagnosis of acute stroke.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: Stroke is a neurological emergency requiring rapid, accurate diagnosis to prevent severe consequences. Early diagnosis is crucial for reducing morbidity and mortality. Artificial intelligence (AI) diagnosis support tools, such as Chat Genera...

Machine learning-assisted diagnosis of parotid tumor by using contrast-enhanced CT imaging features.

Journal of stomatology, oral and maxillofacial surgery
PURPOSE: This study aims to develop a machine learning diagnostic model for parotid gland tumors based on preoperative contrast-enhanced CT imaging features to assist in clinical decision-making.

Super-Resolving and Denoising 4D flow MRI of Neurofluids Using Physics-Guided Neural Networks.

Annals of biomedical engineering
PURPOSE: To obtain high-resolution velocity fields of cerebrospinal fluid (CSF) and cerebral blood flow by applying a physics-guided neural network (div-mDCSRN-Flow) to 4D flow MRI.

Mammography classification with multi-view deep learning techniques: Investigating graph and transformer-based architectures.

Medical image analysis
The potential and promise of deep learning systems to provide an independent assessment and relieve radiologists' burden in screening mammography have been recognized in several studies. However, the low cancer prevalence, the need to process high-re...

Serum targeted metabolomics uncovering specific amino acid signature for diagnosis of intrahepatic cholangiocarcinoma.

Journal of pharmaceutical and biomedical analysis
Intrahepatic cholangiocarcinoma (iCCA) is a hepatobiliary malignancy which accounts for approximately 5-10 % of primary liver cancers and has a high mortality rate. The diagnosis of iCCA remains significant challenges owing to the lack of specific an...

Comprehensive Clinical Usability-Oriented Contour Quality Evaluation for Deep Learning Auto-segmentation: Combining Multiple Quantitative Metrics Through Machine Learning.

Practical radiation oncology
PURPOSE: The current commonly used metrics for evaluating the quality of auto-segmented contours have limitations and do not always reflect the clinical usefulness of the contours. This work aims to develop a novel contour quality classification (CQC...

Artificial Intelligence-Enhanced Risk Stratification of Cancer Therapeutics-Related Cardiac Dysfunction Using Electrocardiographic Images.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intelligence (AI) to...

Enhancing metastatic colorectal cancer prediction through advanced feature selection and machine learning techniques.

International immunopharmacology
BACKGROUND AND AIMS: Colorectal cancer (CRC) is the third most prevalent cancer globally, posing a significant challenge due to its high rate of metastasis. Approximately 20% of patients with CRC present with distant metastases at diagnosis, and over...