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Expert-augmented machine learning for predicting extubation readiness in the pediatric intensive care unit.

BMC medical informatics and decision making
BACKGROUND: Determining extubation readiness in pediatric intensive care units (PICU) is challenging. We used expert-augmented machine learning (EAML), a method that combines machine learning with human expert knowledge, to predict successful extubat...

Physiological serum uric acid concentrations correlate with arterial stiffness in a sex-dependent manner.

BMC medicine
BACKGROUND: In humans, uric acid is a product of purine metabolism that impacts the vascular system. In addition to effects on arterial vascular tone, associations between serum uric acid concentrations-even in the physiological range-and arterial hy...

Can mutation abundance assess the biological behavior of BRAF-positive papillary thyroid carcinoma?

Journal of translational medicine
BACKGROUND: BRAF mutation is the most common genetic change in papillary thyroid carcinoma (PTC). Nevertheless, the association between BRAF mutation status and abundance and the biological behavior of PTC is unclear. Thus, this study investigated wh...

Exploring the possibilities and limitations of customized large language model to support and improve cervical cancer screening.

BMC medical informatics and decision making
BACKGROUND: The rapid advancement of artificial intelligence, driven by Generative Pre-trained Transformers (GPT), has transformed natural language processing. Prompt engineering plays a key role in guiding model outputs effectively. Our primary obje...

The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules.

BMC cancer
BACKGROUND AND AIMS: More cases of thyroid micro-nodules have been diagnosed annually in recent years because of advancements in diagnostic technologies and increased public health awareness. To explore the application value of various machine learni...

Plasma Lyso-PE 22:6 and Lyso-PE 20:4 are associated with development of mild to moderate depression revealed by metabolomics: a pilot study.

BMC psychiatry
BACKGROUND: Mild to moderate depression (MMD), as an early stage of depression, has a high incidence and may progress to severe depression, even leading to suicide. The lack of effective screening and treatment is due to the unknown metabolic changes...

Student perceptions of GenAI as a virtual tutor to support collaborative research training for health professionals.

BMC medical education
BACKGROUND: Research and evaluation skills are essential in healthcare education. Instructors frequently employ collaborative learning models to teach these competencies; however, delivering timely and personalized feedback to multiple groups can be ...

Preoperative MRI-based deep learning reconstruction and classification model for assessing rectal cancer.

BMC medical imaging
BACKGROUND: To determine whether deep learning reconstruction (DLR) could improve the image quality of rectal MR images, and to explore the discrimination of the TN stage of rectal cancer by different readers and deep learning classification models, ...

Large language models versus traditional textbooks: optimizing learning for plastic surgery case preparation.

BMC medical education
BACKGROUND: Large language models (LLMs), such as ChatGPT-4 and Gemini, represent a new frontier in surgical education by offering dynamic, interactive learning experiences. Despite their potential, concerns about the accuracy, depth of knowledge, an...

Deep learning-based automated classification of choroidal layers in en face swept-source optical coherence tomography images.

BMC ophthalmology
BACKGROUND: This study aims to develop a deep learning-based algorithm dedicated to the automated classification of choroidal layers in en face swept-source optical coherence tomography (SS-OCT) images of the eye.