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Algorithmic Identification of Treatment-Emergent Adverse Events From Clinical Notes Using Large Language Models: A Pilot Study in Inflammatory Bowel Disease.

Clinical pharmacology and therapeutics
Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmacovigilance due to methodological limitations in text mining. Large language models (LLMs) like Bidir...

Development of Machine Learning Models for the Identification of Elevated Ketone Bodies During Hyperglycemia in Patients with Type 1 Diabetes.

Diabetes technology & therapeutics
Diabetic ketoacidosis (DKA) is a serious life-threatening condition caused by a lack of insulin, which leads to elevated plasma glucose and metabolic acidosis. Early identification of developing DKA is important to start treatment and minimize compl...

Ethics for AI in Plastic Surgery: Guidelines and Review.

Aesthetic plastic surgery
INTRODUCTION: Artificial intelligence (AI) holds the potential to revolutionize medicine, offering vast improvements for plastic surgery. While human physicians are limited to one lifetime of experience, AI is poised to soon surpass human capabilitie...

Improving the detection of hypo-vascular liver metastases in multiphase contrast-enhanced CT with slice thickness less than 5 mm using DenseNet.

Radiography (London, England : 1995)
INTRODUCTION: Thinner slices are more susceptible in detecting small lesions but suffer from higher statistical fluctuation. This work aimed to reduce image noise in multiphase contrast-enhanced CT reconstructed with slice thickness thinner than the ...

Mining phase separation-related diagnostic biomarkers for endometriosis through WGCNA and multiple machine learning techniques: a retrospective and nomogram study.

Journal of assisted reproduction and genetics
OBJECTIVE: The objective of this study was to investigate the role of phase separation-related genes in the development of endometriosis (EMs) and to identify potential characteristic genes associated with the condition.

Research on Human-Robot Collaboration Method for Parallel Robots Oriented to Segment Docking.

Sensors (Basel, Switzerland)
In the field of aerospace, large and heavy cabin segments present a significant challenge in assembling space engines. The substantial inertial force of cabin segments' mass often leads to unexpected motion during docking, resulting in segment collis...

Nursing Perceptions of Robotic Technology in Healthcare: A Pretest-Posttest Survey Analysis Using an Educational Video.

IISE transactions on occupational ergonomics and human factors
OCCUPATIONAL APPLICATIONSWe used a survey to evaluate the perceptions of nurses and nursing students on robotic technology for nursing care before and after reviewing an educational video that included examples of medical, care, and healthcare servic...

Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients.

ANZ journal of surgery
BACKGROUND: The treatment of locally advanced rectal cancer (LARC) is moving towards total neoadjuvant therapy and potential organ preservation. Of particular interest are predictors of pathological complete response (pCR) that can guide personalized...

ChatGPT and Patients With Heart Failure.

Angiology
ChatGPT (Generative Pre-trained Transformer) is a large-scale language processing model, with possibilities for professional patient support in a patient-friendly way. The aim of the study was to examine the accuracy and reproducibility of ChatGPT in...

Development and external validation of a machine learning model for prediction of survival in extremity leiomyosarcoma.

Surgical oncology
PURPOSE: Machine learning (ML) models have been used to predict cancer survival in several sarcoma subtypes. However, none have investigated extremity leiomyosarcoma (LMS). ML is a powerful tool that has the potential to better prognosticate extremit...