AIMC Topic: Humans

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Improving Clinical Documentation with Artificial Intelligence: A Systematic Review.

Perspectives in health information management
Clinicians dedicate significant time to clinical documentation, incurring opportunity cost. Artificial Intelligence (AI) tools promise to improve documentation quality and efficiency. This systematic review overviews peer-reviewed AI tools to underst...

Surgical factors play a critical role in predicting functional outcomes using machine learning in robotic-assisted total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Predictive models help determine predictive factors necessary to improve functional outcomes after total knee arthroplasty (TKA). However, no study has assessed predictive models for functional outcomes after TKA based on the new concepts of...

Prediction of surgery-first approach orthognathic surgery using deep learning models.

International journal of oral and maxillofacial surgery
The surgery-first approach (SFA) orthognathic surgery can be beneficial due to reduced overall treatment time and earlier profile improvement. The objective of this study was to utilize deep learning to predict the treatment modality of SFA or the or...

Tricuspid valve flow measurement using a deep learning framework for automated valve-tracking 2D phase contrast.

Magnetic resonance in medicine
PURPOSE: Tricuspid valve flow velocities are challenging to measure with cardiovascular MR, as the rapidly moving valvular plane prohibits direct flow evaluation, but they are vitally important to diastolic function evaluation. We developed an automa...

A review of uncertainty quantification in medical image analysis: Probabilistic and non-probabilistic methods.

Medical image analysis
The comprehensive integration of machine learning healthcare models within clinical practice remains suboptimal, notwithstanding the proliferation of high-performing solutions reported in the literature. A predominant factor hindering widespread adop...

Unsupervised domain adaptation with weak source domain labels via bidirectional subdomain alignment.

Neural networks : the official journal of the International Neural Network Society
Unsupervised domain adaptation (UDA) enables knowledge transfer from a labeled source domain to an unlabeled target domain. However, UDA performance often relies heavily on the accuracy of source domain labels, which are frequently noisy or missing i...

KEMoS: A knowledge-enhanced multi-modal summarizing framework for Chinese online meetings.

Neural networks : the official journal of the International Neural Network Society
The demand for "online meetings" and "collaborative office work" keeps surging recently, producing an abundant amount of relevant data. How to provide participants with accurate and fast summarizing service has attracted extensive attention. Existing...

Machine learning models based on ultrasound and physical examination for airway assessment.

Revista espanola de anestesiologia y reanimacion
PURPOSE: To demonstrate the utility of machine learning models for predicting difficult airways using clinical and ultrasound parameters.

Revolutionizing Cardiology With Words: Unveiling the Impact of Large Language Models in Medical Science Writing.

The Canadian journal of cardiology
Large language models (LLMs) are a unique form of machine learning that facilitates inputs of unstructured text/numerical information for meaningful interpretation and prediction. Recently, LLMs have become commercialized, allowing the average person...

Validity of facial skin analysis pore detection: A comparative analysis.

Journal of cosmetic dermatology
BACKGROUND: Reliable, objective measures to assess facial characteristics would aid in the assessment of many dermatological treatments. Previous work utilized an iOS application-based artificial intelligence (AI) tool compared to the "gold standard"...