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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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English 日本語
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English 日本語
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MYU K.K.
Sensors and Materials
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The Art of Writing Scientific Papers
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 31, Number 3(3) (2019)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 883-888
S&M1822 Research Paper of Special Issue https://doi.org/10.18494/SAM.2019.2095 Published: March 29, 2019 Performance Improvement of Ovarian Cancer Classification Model Using Multiple Biomarkers and Menopause Information [PDF] Hye-Jeong Song, Min-Sun Kyung, Eun-Suk Yang, Jong-Dae Kim, Chan-Young Park, and Yu-Seop Kim (Received May 31, 2018; Accepted January 8, 2019) Keywords: ovarian cancer, IVDMIA, marker combination, cancer classification, menopause
The tumor biomarker test used for the early diagnosis of ovarian cancer is a relatively simple test using blood. In previous studies, an optimal combination of 2 or 3 biomarkers from 16 cancer biomarkers showing a specific response to ovarian cancer was designed to obtain an ovarian cancer classification model. Menopause is an important information for diagnosing ovarian cancer. In this study, we applied the menopausal status to the classification model and confirmed the performance results. The classification model has better performance when including menopausal clinical information.
Corresponding author: Min-Sun Kyung  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Hye-Jeong Song, Min-Sun Kyung, Eun-Suk Yang, Jong-Dae Kim, Chan-Young Park, and Yu-Seop Kim, Performance Improvement of Ovarian Cancer Classification Model Using Multiple Biomarkers and Menopause Information, Sens. Mater., Vol. 31, No. 3, 2019, p. 883-888. |
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- Deep Learning Prediction Model of Mortality Including Brain-type Natriuretic Peptide in Patients with Acute Decompensated Heart Failure
Hirotaka Takizawa, Masatoshi Minamisawa, Hirohiko Motoki, Koichiro Kuwahara, and Masaki Yamaguchi
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