Results 331 to 340 of about 28,602,314 (397)

Quantitative Iron Measurements in the Basal Ganglia of NBIA Patients Using QSM: Insights From a Tertiary Center

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Neurodegeneration with brain iron accumulation (NBIA) comprises rare genetic disorders characterized by predominantly extrapyramidal symptoms and iron deposition in the basal ganglia. Conventional magnetic resonance imaging (MRI) detects qualitative changes but cannot accurately quantify iron accumulation. Quantitative susceptibility
Özge Uygun, Alpay Özcan, Fuat Kaan Aras, Evrim Bozdemir, Sibel Uğur İşeri, Koray Kırımtay, Arzu Karabay, Murat Gültekin, Nihan Hande Akçakaya, Orkhan Mammadov, Gülay Kır, Dilek İnce Günal, Neşe Tuncer, Fatma Betül Özdilek, Banu Özen Barut, Ercan Köse, Hülya Apaydın, Asuman Ali, Sultan Çağırıcı, Pınar Topaloğlu, Alp Dinçer, Zuhal Yapıcı   +21 more
wiley   +1 more source

Commentary on “The Impact of Diabetes and Metabolic Syndrome Burden on Pain, Neuropathy Severity and Fiber Type”

Annals of Clinical and Translational Neurology, EarlyView.
Majid Khalilizad, Ebrahim Hejazian, Mohammad Barary, Mostafa Javanian, Soheil Ebrahimpour   +4 more
wiley   +1 more source

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Advances in the Application of Artificial Intelligence-Based Spectral Data Interpretation: A Perspective.

Analytical Chemistry, 2023
The interpretation of spectral data, including mass, nuclear magnetic resonance, infrared, and ultraviolet-visible spectra, is critical for obtaining molecular structural information.
Xi Xue, Hanyu Sun, Minjian Yang, Xue Liu, Hai‐Yu Hu, Yafeng Deng, Xiaojian Wang   +6 more
semanticscholar   +1 more source

Soil Organic Matter Characterization by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR MS): A Critical Review of Sample Preparation, Analysis, and Data Interpretation.

Environmental Science and Technology, 2021
The biogeochemical cycling of soil organic matter (SOM) plays a central role in regulating soil health, water quality, carbon storage, and greenhouse gas emissions.
William Bahureksa, M. Tfaily, R. Boiteau, Robert B. Young, Merritt N. Logan, A. McKenna, T. Borch   +6 more
semanticscholar   +1 more source

Distributed Deep Learning for Remote Sensing Data Interpretation

Proceedings of the IEEE, 2021
As a newly emerging technology, deep learning (DL) is a very promising field in big data applications. Remote sensing often involves huge data volumes obtained daily by numerous in-orbit satellites.
J. Haut, Mercedes Eugenia Paoletti, S. Moreno-Álvarez, J. Plaza, Juan A. Rico-Gallego, A. Plaza   +5 more
semanticscholar   +1 more source

Data Interpretation

Evaluations of Police Suitability and Fitness for Duty, 2020
This chapter begins with a discussion of the benefits of using a data integration model to guide clinical decision-making in suitability and fitness evaluations.
David M. Corey, M. Zelig
semanticscholar   +3 more sources

CoDa: Collaborative Data Interpretation Through an Interactive Tangible Scatterplot

International Conference on Tangible, Embedded, and Embodied Interaction, 2020
Tangibles can model abstract structures. One educational subject where this can be utilized is instruction on data visualization inter- pretation.
A. Veldhuis, Rong-Hao Liang, M. M. Bekker   +2 more
semanticscholar   +1 more source

Interpreting the data

2022
Chapter 4 provides a comparative quantitative analysis of Ireland with the largest economies in Europe (EU15), drawing on EU and OECD surveys for food poverty and UN for food insecurity. The chapter also builds on existing quantitative research to provide an updated analysis of food poverty in Ireland, using the latest secondary data available.
openaire   +1 more source

Storytelling, business analytics and big data interpretation

Management Research Review, 2019
Purpose The purpose of this paper is to explore the role of storytelling in data interpretation, decision-making and individual-level adoption of business analytics (BA).
Valeriia Boldosova, S. Luoto
semanticscholar   +1 more source

The interpretation of genetical data

Experientia, 1957
Fur die Interpretation genetischer Ergebnisse wird den Autoren vorgeschlagen, Grundannahmen jeweils ausfuhrlich zu formulieren.
E. E. Shult, Carl C. Lindegren
openaire   +3 more sources