AI Medical Compendium Topic:
Reproducibility of Results

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Artificial Intelligence in Otolaryngology: Topics in Epistemology & Ethics.

Otolaryngologic clinics of North America
To fuel artificial intelligence (AI) potential in clinical practice in otolaryngology, researchers must understand its epistemic limitations, which are tightly linked to ethical dilemmas requiring careful consideration. AI tools are fundamentally opa...

Reliability of artificial intelligence chatbot responses to frequently asked questions in breast surgical oncology.

Journal of surgical oncology
INTRODUCTION: Artificial intelligence (AI)-driven chatbots, capable of simulating human-like conversations, are becoming more prevalent in healthcare. While this technology offers potential benefits in patient engagement and information accessibility...

Comparison Between an Expert Operator an Inexperienced Operator, and Artificial Intelligence Software: A Brief Clinical Study of Cephalometric Diagnostic.

The Journal of craniofacial surgery
INTRODUCTION: Artificial intelligence (AI) is constantly developing in several medical areas and has become useful to assist with treatment planning. Orthodontics and maxillofacial surgery use AI-based technology to identify and select cephalometric ...

Deep Learning-Based Approach for Identifying and Measuring Focal Liver Lesions on Contrast-Enhanced MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The number of focal liver lesions (FLLs) detected by imaging has increased worldwide, highlighting the need to develop a robust, objective system for automatically detecting FLLs.

Classification of short and long term mild traumatic brain injury using computerized eye tracking.

Scientific reports
Accurate, and objective diagnosis of brain injury remains challenging. This study evaluated useability and reliability of computerized eye-tracker assessments (CEAs) designed to assess oculomotor function, visual attention/processing, and selective a...

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...

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"...

Deep Learning-Based Segmentation and Risk Stratification for Gastrointestinal Stromal Tumors in Transabdominal Ultrasound Imaging.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
PURPOSE: To develop a deep neural network system for the automatic segmentation and risk stratification prediction of gastrointestinal stromal tumors (GISTs).