Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 1, 2025
The automatic screening of thyroid nodules using computer-aided diagnosis holds great promise in reducing missed and misdiagnosed cases in clinical practice. However, most current research focuses on single-modal images and does not fully leverage th...
PURPOSE: To develop and validate interpretable machine learning models for differentiating glioblastoma (GB) from solitary brain metastasis (SBM) using radiomics features from contrast-enhanced T1-weighted MRI (CE-T1WI), and to compare the impact of ...
RATIONALE AND OBJECTIVES: Early detection of malignant lesions in ultrasound images is crucial for effective cancer diagnosis and treatment. While traditional methods rely on radiologists, deep learning models can improve accuracy, reduce errors, and...
IEEE transactions on pattern analysis and machine intelligence
Sep 1, 2025
Eye-tracking is a reliable method for quantifying visual information processing and holds significant potential for group recognition, such as identifying autism spectrum disorder (ASD). However, eye-tracking research typically faces the heterogeneit...
Preterm birth and very low birthweight (VP/VLBW) are associated with poorer health-related quality of life (HRQoL) outcomes extending into adulthood, yet it remains unclear how these effects differ across sociodemographic subgroups. This study aimed ...
BJOG : an international journal of obstetrics and gynaecology
Sep 1, 2025
OBJECTIVE: To create and validate a machine learning (ML)-based model for predicting the adverse perinatal outcome (APO) in foetal growth restriction (FGR) at diagnosis.
BACKGROUND: The use of digital technologies is becoming increasingly important in medicine and is having a significant impact on developments in the surgical field. However, there is a great need to improve and implement those new techniques in surgi...
BackgroundThe rapid advancement of Artificial Intelligence (AI) is driving transformative changes across various sectors, reshaping organizational management models and altering work dynamics for employees.ObjectiveThis study employs the framework of...
Journal of minimally invasive gynecology
Sep 1, 2025
OBJECTIVE: To evaluate the predictive value of clinical features in the diagnosis of endometriosis by utilizing machine learning algorithms (MLAs), aiming to develop an accurate, explainable prediction model.
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