AIMC Topic: Reproducibility of Results

Clear Filters Showing 1381 to 1390 of 5908 articles

Large Language Models for Therapy Recommendations Across 3 Clinical Specialties: Comparative Study.

Journal of medical Internet research
BACKGROUND: As advancements in artificial intelligence (AI) continue, large language models (LLMs) have emerged as promising tools for generating medical information. Their rapid adaptation and potential benefits in health care require rigorous asses...

Significant wave height prediction from X-band marine radar images using deep learning with 3D convolutions.

PloS one
This research introduces a deep learning method for ocean wave height estimation utilizing a Convolutional Neural Network (CNN) based on the VGGNet. The model is trained on a dataset comprising buoy wave heights and radar images, both critical for ma...

Eye-Gaze-Guided Vision Transformer for Rectifying Shortcut Learning.

IEEE transactions on medical imaging
Learning harmful shortcuts such as spurious correlations and biases prevents deep neural networks from learning meaningful and useful representations, thus jeopardizing the generalizability and interpretability of the learned representation. The situ...

A Perifacial EMG Acquisition System for Facial-Muscle-Movement Recognition.

Sensors (Basel, Switzerland)
This paper proposes a portable wireless transmission system for the multi-channel acquisition of surface electromyography (EMG) signals. Because EMG signals have great application value in psychotherapy and human-computer interaction, this system is ...

Improving on in-silico prediction of oral drug bioavailability.

Expert opinion on drug metabolism & toxicology
INTRODUCTION: Although significant development has been made in high-throughput screening of oral drug absorption and oral bioavailability, prediction continues to play an important role in prediction of oral bioavailability and assisting in the pro...

SpheroScan: a user-friendly deep learning tool for spheroid image analysis.

GigaScience
BACKGROUND: In recent years, 3-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has...

Cephalometric analysis performance discrepancy between orthodontists and an artificial intelligence model using lateral cephalometric radiographs.

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
PURPOSE: The purpose of the present clinical study was to compare the Ricketts and Steiner cephalometric analysis obtained by two experienced orthodontists and artificial intelligence (AI)-based software program and measure the orthodontist variabili...

Laypersons versus experienced surgeons in assessing simulated robot-assisted radical prostatectomy.

World journal of urology
BACKGROUND: Feedback is important for surgical trainees but it can be biased and time-consuming. We examined crowd-sourced assessment as an alternative to experienced surgeons' assessment of robot-assisted radical prostatectomy (RARP).

Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: "Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability.

On-Device Execution of Deep Learning Models on HoloLens2 for Real-Time Augmented Reality Medical Applications.

Sensors (Basel, Switzerland)
The integration of Deep Learning (DL) models with the HoloLens2 Augmented Reality (AR) headset has enormous potential for real-time AR medical applications. Currently, most applications execute the models on an external server that communicates with ...