Zobrazeno 1 - 10
of 102
pro vyhledávání: '"Daniel K Park"'
Autor:
Anthony Russo, Daniel K Park, Todd Lansford, Pierce Nunley, Timothy A Peppers, Joshua J Wind, Hamid Hassanzadeh, Joseph Sembrano, Jung Yoo, Jonathan Sales
Publikováno v:
BMC Musculoskeletal Disorders, Vol 25, Iss 1, Pp 1-9 (2024)
Abstract Background The current report investigates fusion rates and patient-reported outcomes following lumbar spinal surgery using cellular bone allograft (CBA) in patients with risk factors for non-union. Methods A prospective, open label study wa
Externí odkaz:
https://doaj.org/article/d7d0434def4642619f542d5253bdff44
Publikováno v:
North American Spine Society Journal, Vol 17, Iss , Pp 100314- (2024)
ABSTRACT: Background: There is growing interest in transitioning various surgical procedures to the outpatient care setting. However, for Medicare patients, the site of service for surgical procedures is influenced by regulations within the Inpatient
Externí odkaz:
https://doaj.org/article/00a4f4b04c204827abcea430e4976276
Autor:
Hyeondo Oh, Daniel K Park
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 3, p 035052 (2024)
Anomaly detection is a critical problem in data analysis and pattern recognition, finding applications in various domains. We introduce quantum support vector data description (QSVDD), an unsupervised learning algorithm designed for anomaly detection
Externí odkaz:
https://doaj.org/article/804d35ab11d84723a8c379a68c46e543
Autor:
Changwon Lee, Daniel K Park
Publikováno v:
Machine Learning: Science and Technology, Vol 4, Iss 4, p 045051 (2023)
Mitigating measurement errors in quantum systems without relying on quantum error correction is of critical importance for the practical development of quantum technology. Deep learning-based quantum measurement error mitigation (QMEM) has exhibited
Externí odkaz:
https://doaj.org/article/a7616ca19e034ebdbd43c043bf1e70c5
Publikováno v:
Machine Learning: Science and Technology, Vol 4, Iss 1, p 015006 (2023)
One-class classification (OCC) is a fundamental problem in pattern recognition with a wide range of applications. This work presents a semi-supervised quantum machine learning algorithm for such a problem, which we call a variational quantum one-clas
Externí odkaz:
https://doaj.org/article/1bf036b1f9d94a678a36ca9d60467a38
Publikováno v:
New Journal of Physics, Vol 24, Iss 7, p 073009 (2022)
Quantum computing devices are inevitably subject to errors. To leverage quantum technologies for computational benefits in practical applications, quantum algorithms and protocols must be implemented reliably under noise and imperfections. Since nois
Externí odkaz:
https://doaj.org/article/54bf6c590f844a64a76d33a03ee0f0c2
Publikováno v:
New Journal of Physics, Vol 21, Iss 8, p 083024 (2019)
The computational cost of preparing a quantum state can be substantial depending on the structure of data to be encoded. Many quantum algorithms require repeated sampling to find the answer, mandating reconstruction of the same input state for every
Externí odkaz:
https://doaj.org/article/ed42c0a427514fadbf0eb1fed392595a
Publikováno v:
Orthopedic Research and Reviews, Vol 2009, Iss Default, Pp 11-21 (2009)
Justin Munns, Daniel K Park, Kern SinghDepartment of Orthopedic Surgery, Rush University Medical Center, Chicago, Illinois, USAAbstract: Osteogenic protein-1 (OP-1), also known as bone morphogenetic protein-7 (BMP-7), is a protein in the TGF-β famil
Externí odkaz:
https://doaj.org/article/7482aa68aeac41309099b1d5ff751f14
Publikováno v:
npj Quantum Information, Vol 7, Iss 1, Pp 1-9 (2021)
Abstract Discrete stochastic processes (DSP) are instrumental for modeling the dynamics of probabilistic systems and have a wide spectrum of applications in science and engineering. DSPs are usually analyzed via Monte-Carlo methods since the number o
Externí odkaz:
https://doaj.org/article/70ee040d9b934c0c89b96c9c4ff0fd91
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Abstract Advantages in several fields of research and industry are expected with the rise of quantum computers. However, the computational cost to load classical data in quantum computers can impose restrictions on possible quantum speedups. Known al
Externí odkaz:
https://doaj.org/article/a136e05410b94f9092cfe162388ad960