AI Medical Compendium Topic:
Reproducibility of Results

Clear Filters Showing 971 to 980 of 5495 articles

ChatGPT vs UpToDate: comparative study of usefulness and reliability of Chatbot in common clinical presentations of otorhinolaryngology-head and neck surgery.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: The usage of Chatbots as a kind of Artificial Intelligence in medicine is getting to increase in recent years. UpToDate® is another well-known search tool established on evidence-based knowledge and is used daily by doctors worldwide. In thi...

Deep Learning-Based Analysis of Aortic Morphology From Three-Dimensional MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Quantification of aortic morphology plays an important role in the evaluation and follow-up assessment of patients with aortic diseases, but often requires labor-intensive and operator-dependent measurements. Automatic solutions would hel...

A Practical Guide to Phage- and Robotics-assisted Near-continuous Evolution.

Journal of visualized experiments : JoVE
Robotics-accelerated Evolution techniques improve the reliability and speed of evolution using feedback control, improving the outcomes of protein and organism evolution experiments. In this article, we present a guide to setting up the hardware and ...

Deep learning-based cerebral aneurysm segmentation and morphological analysis with three-dimensional rotational angiography.

Journal of neurointerventional surgery
BACKGROUND: The morphological assessment of cerebral aneurysms based on cerebral angiography is an essential step when planning strategy and device selection in endovascular treatment, but manual evaluation by human raters only has moderate interrate...

Glenohumeral joint force prediction with deep learning.

Journal of biomechanics
Deep learning models (DLM) are efficient replacements for computationally intensive optimization techniques. Musculoskeletal models (MSM) typically involve resource-intensive optimization processes for determining joint and muscle forces. Consequentl...

MRI-Based Kinetic Heterogeneity Evaluation in the Accurate Access of Axillary Lymph Node Status in Breast Cancer Using a Hybrid CNN-RNN Model.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Accurate evaluation of the axillary lymph node (ALN) status is needed for determining the treatment protocol for breast cancer (BC). The value of magnetic resonance imaging (MRI)-based tumor heterogeneity in assessing ALN metastasis in BC...

Pragmatic Evaluation of a Deep-Learning Algorithm to Automate Ejection Fraction on Hand-Held, Point-of-Care Echocardiography in a Cardiac Surgical Operating Room.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVE: To test the correlation of ejection fraction (EF) estimated by a deep-learning-based, automated algorithm (Auto EF) versus an EF estimated by Simpson's method.

Repeatability, reproducibility, and diagnostic accuracy of a commercial large language model (ChatGPT) to perform emergency department triage using the Canadian triage and acuity scale.

CJEM
PURPOSE: The release of the ChatGPT prototype to the public in November 2022 drastically reduced the barrier to using artificial intelligence by allowing easy access to a large language model with only a simple web interface. One situation where Chat...

A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future.

Osteoarthritis and cartilage
OBJECTIVE: This perspective describes the evolution of semi-quantitative (SQ) magnetic resonance imaging (MRI) in characterizing structural tissue pathologies in osteoarthritis (OA) imaging research over the last 30 years.

TISBE: A Public Web Platform for the Consensus-Based Explainable Prediction of Developmental Toxicity.

Chemical research in toxicology
Despite being extremely relevant for the protection of prenatal and neonatal health, the developmental toxicity (Dev Tox) is a highly complex endpoint whose molecular rationale is still largely unknown. The lack of availability of high-quality data a...