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Explainable artificial intelligence for prediction of refractory ulcerative colitis: analysis of a Japanese Nationwide Registry.

Annals of medicine
OBJECTIVE: Ulcerative colitis (UC) is a chronic inflammatory bowel disease for which remission is dependent on corticosteroid (CS) treatment. The diversity of disease pathophysiology necessitates optimal case-specific treatment selection. This study ...

Surgical and radiological outcomes of giant cell tumor of the bone: prognostic value of Campanacci grading and selective use of denosumab.

Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology
BACKGROUND: Advancements in diagnostic and therapeutic modalities for giant cell tumors of bone (GCTB) have introduced molecular and radiological tools that refine clinical decision-making. H3.3 G34W immunohistochemical staining has become a routine ...

Is AI the future of evaluation in medical education?? AI vs. human evaluation in objective structured clinical examination.

BMC medical education
BACKGROUND: Objective Structured Clinical Examinations (OSCEs) are widely used in medical education to assess students' clinical and professional skills. Recent advancements in artificial intelligence (AI) offer opportunities to complement human eval...

Perspectives and Experiences With Large Language Models in Health Care: Survey Study.

Journal of medical Internet research
BACKGROUND: Large language models (LLMs) are transforming how data is used, including within the health care sector. However, frameworks including the Unified Theory of Acceptance and Use of Technology highlight the importance of understanding the fa...

Identifying high-dose opioid prescription risks using machine learning: A focus on sociodemographic characteristics.

Journal of opioid management
OBJECTIVE: The objective of this study was to leverage machine learning techniques to analyze administrative claims and socioeconomic data, with the aim of identifying and interpreting the risk factors associated with high-dose opioid prescribing.

Adopting machine learning to predict nomogram for small incision lenticule extraction (SMILE).

International ophthalmology
PURPOSE: To predict nomogram for small incision lenticule extraction (SMILE) using machine learning technology and preoperative clinical data.

Effects of exoskeleton rehabilitation robot training on neuroplasticity and lower limb motor function in patients with stroke.

BMC neurology
BACKGROUND: Lower limb exoskeleton rehabilitation robot is a new technology to improve the lower limb motor function of stroke patients. Recovery of motor function after stroke is closely related to neuroplasticity in the motor cortex and associated ...

A deep learning algorithm for automated adrenal gland segmentation on non-contrast CT images.

BMC medical imaging
BACKGROUND: The adrenal glands are small retroperitoneal organs, few reference standards exist for adrenal CT measurements in clinical practice. This study aims to develop a deep learning (DL) model for automated adrenal gland segmentation on non-con...

Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome.

BMC medical informatics and decision making
BACKGROUND AND OBJECTIVE: This study has two main objectives. First, to evaluate a feature selection methodology based on SEQENS, an algorithm for identifying relevant variables. Second, to validate machine learning models that predict the risk of co...