Application of Machine Learning Methods in NPH

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F23%3A00370036" target="_blank" >RIV/68407700:21730/23:00370036 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1007/978-3-031-36522-5_19" target="_blank" >https://doi.org/10.1007/978-3-031-36522-5_19</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-36522-5_19" target="_blank" >10.1007/978-3-031-36522-5_19</a>

Result language

angličtina

Original language name

Application of Machine Learning Methods in NPH

Original language description

The chapter explores the use of machine learning (ML) in Normal Pressure Hydrocephalus (NPH) diagnosis and treatment. It delves into various ML techniques, such as artificial neural networks and decision trees, for analyzing medical data, particularly in predictive medicine. The chapter also discusses different ML learning problems, feature extraction and selection in clinical datasets, and the evaluation of ML models using standard diagnostic tests. It also highlights limitations and potential biases in ML applications in neurosurgery. Additionally, the article provides insights into specific applications, including lumbar infusion test-based data and phase-contrast MRI-based data, and reviews other ML studies in NPH, showcasing the diverse approaches and methodologies employed in the field.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/NU23-04-00551" target="_blank" >NU23-04-00551: A Complex Multi-layer Diagnostic Battery for NPH</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů