Výsledky vyhledávání - "George, Eckert"

Akademický článek

Short- and Long-Term Prediction of the Post-Pubertal Mandibular Length and Y-Axis in Females Utilizing Machine Learning

Autor: Matthew Parrish, Ella O’Connell, George Eckert, Jay Hughes, Sarkhan Badirli, Hakan Turkkahraman

Publikováno v: Diagnostics, Vol 13, Iss 17, p 2729 (2023)

The aim of this study was to create a novel machine learning (ML) algorithm for predicting the post-pubertal mandibular length and Y-axis in females. Cephalometric data from 176 females with Angle Class I occlusion were used to train and test seven M

Externí odkaz: https://doaj.org/article/a4252386b04a49dc823f18bd836deb01

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

A Novel Machine Learning Model for Predicting Orthodontic Treatment Duration

Autor: James Volovic, Sarkhan Badirli, Sunna Ahmad, Landon Leavitt, Taylor Mason, Surya Sruthi Bhamidipalli, George Eckert, David Albright, Hakan Turkkahraman

Publikováno v: Diagnostics, Vol 13, Iss 17, p 2740 (2023)

In the field of orthodontics, providing patients with accurate treatment time estimates is of utmost importance. As orthodontic practices continue to evolve and embrace new advancements, incorporating machine learning (ML) methods becomes increasingl

Externí odkaz: https://doaj.org/article/c54e4891c3ff4c40b6747023581d75c0

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Prediction of Pubertal Mandibular Growth in Males with Class II Malocclusion by Utilizing Machine Learning

Autor: Grant Zakhar, Samir Hazime, George Eckert, Ariel Wong, Sarkhan Badirli, Hakan Turkkahraman

Publikováno v: Diagnostics, Vol 13, Iss 16, p 2713 (2023)

The goal of this study was to create a novel machine learning (ML) model that can predict the magnitude and direction of pubertal mandibular growth in males with Class II malocclusion. Lateral cephalometric radiographs of 123 males at three time poin

Externí odkaz: https://doaj.org/article/d94e69bc300946d99b07068a7e87124a

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Precision and Accuracy Assessment of Cephalometric Analyses Performed by Deep Learning Artificial Intelligence with and without Human Augmentation

Autor: Sumer Panesar, Alyssa Zhao, Eric Hollensbe, Ariel Wong, Surya Sruthi Bhamidipalli, George Eckert, Vinicius Dutra, Hakan Turkkahraman

Publikováno v: Applied Sciences, Vol 13, Iss 12, p 6921 (2023)

The aim was to assess the precision and accuracy of cephalometric analyses performed by artificial intelligence (AI) with and without human augmentation. Four dental professionals with varying experience levels identified 31 landmarks on 30 cephalome

Externí odkaz: https://doaj.org/article/934e23619d214ff1948b3c6e36e85221

Zobrazit plný text záznamu

Akademický článek

Prediction of the Post-Pubertal Mandibular Length and Y Axis of Growth by Using Various Machine Learning Techniques: A Retrospective Longitudinal Study

Autor: Tyler Wood, Justina O. Anigbo, George Eckert, Kelton T. Stewart, Mehmet Murat Dundar, Hakan Turkkahraman

Publikováno v: Diagnostics, Vol 13, Iss 9, p 1553 (2023)

The aim was to predict the post-pubertal mandibular length and Y axis of growth in males by using various machine learning (ML) techniques. Cephalometric data obtained from 163 males with Class I Angle malocclusion, were used to train various ML algo

Externí odkaz: https://doaj.org/article/6c29a190ebbd48aa90c927bc8ea3e956

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Exploratory Study of Autoantibody Profiling in Drug‐Induced Liver Injury with an Autoimmune Phenotype

Autor: Craig Lammert, Chengsong Zhu, Yun Lian, Indu Raman, George Eckert, Quan‐Zhen Li, Naga Chalasani

Publikováno v: Hepatology Communications, Vol 4, Iss 11, Pp 1651-1663 (2020)

Drug‐induced liver injury (DILI) sometimes presents with an autoimmune hepatitis‐like phenotype (AI‐DILI), and it is challenging to distinguish it from de novo autoimmune hepatitis (AIH). We conducted a study to identify autoantibodies unique t

Externí odkaz: https://doaj.org/article/e824f34207444e2fbfe5b2dc9699f2b7

Zobrazit plný text záznamu

Akademický článek

A Feasibility Study on Mixed Reality-Based Visualization and Interaction Tool for Performance Improvement of Metal Cutting Processes

Autor: Sagil James, George Eckert

Publikováno v: Metals, Vol 13, Iss 2, p 286 (2023)

Modern CNC machining industries rely on the application of high-technology virtual simulations such as Finite Element Analysis (FEA) to become economically competitive, improve productivity, and ensure sustainability. However, the traditional way of

Externí odkaz: https://doaj.org/article/bccf643ee74c4838a9d479fe983b5474

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání