AIMC Topic: Humans

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Can ChatGPT 4.0 reliably answer patient frequently asked questions about boxer's fractures?

Hand surgery & rehabilitation
BACKGROUND: Patients are increasingly turning to the internet, and recently artificial intelligence engines (e.g., ChatGPT), for answers to common medical questions. Regarding orthopedic hand surgery, recent literature has focused on ChatGPT's abilit...

Harnessing NLP to investigate biomarker interactions and CVD risks in elderly chronic kidney disease patients.

SLAS technology
Chronic kidney disease (CKD) significantly increases the risk of CVD diseases, particularly among elderly patients. Understanding the interaction between several biomarkers and cardiovascular (CVD) risks is crucial for improving patient outcomes and ...

Evaluation of Multilingual Simplifications of IR Procedural Reports Using GPT-4.

Journal of vascular and interventional radiology : JVIR
This study assessed the feasibility of large language models such as GPT-4 (OpenAI, San Francisco, California) to summarize interventional radiology procedural reports to improve layperson understanding and translate medical texts into multiple langu...

Performance evaluation of a machine learning-based methodology using dynamical features to detect nonwear intervals in actigraphy data in a free-living setting.

Sleep health
GOAL AND AIMS: One challenge using wearable sensors is nonwear time. Without a nonwear (e.g., capacitive) sensor, actigraphy data quality can be biased by subjective determinations confounding sleep/wake classification. We developed and evaluated a m...

Traditional versus modern approaches to screening mammography: a comparison of computer-assisted detection for synthetic 2D mammography versus an artificial intelligence algorithm for digital breast tomosynthesis.

Breast cancer research and treatment
PURPOSE: Traditional computer-assisted detection (CADe) algorithms were developed for 2D mammography, while modern artificial intelligence (AI) algorithms can be applied to 2D mammography and/or digital breast tomosynthesis (DBT). The objective is to...

Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.

Drug safety
BACKGROUND: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence ...

Automatic medical imaging segmentation via self-supervising large-scale convolutional neural networks.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: This study aims to develop a robust, large-scale deep learning model for medical image segmentation, leveraging self-supervised learning to overcome the limitations of supervised learning and data variability in clinical settings.

Evaluation of machine learning models for predicting xerostomia in adults with head and neck cancer during proton and heavy ion radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Few studies have examined the factors associated with xerostomia during proton and carbon ion radiotherapy for head and neck cancer (HNC), which are reported to have fewer toxic effects compared to traditional photon-based rad...

Unveiling the role of artificial intelligence applied to clear aligner therapy: A scoping review.

Journal of dentistry
OBJECTIVES: To conduct a scoping review on the application of artificial intelligence (AI) in clear aligner therapy and to assess the extent of AI integration and automation in orthodontic software currently available to orthodontists.

Automated stenosis estimation of coronary angiographies using end-to-end learning.

The international journal of cardiovascular imaging
The initial evaluation of stenosis during coronary angiography is typically performed by visual assessment. Visual assessment has limited accuracy compared to fractional flow reserve and quantitative coronary angiography, which are more time-consumin...