Showing 21 - 40 results of 72 for search 'T46 (classification)', query time: 0.08s Refine Results
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    Fourier Descriptor Pada Klasifikasi Daun Herbal Menggunakan Support Vector Machine Dan Naive Bayes by Mutmainnah Samir, Purnawansyah, Herdianti Darwis, Fitriyani Umar

    Published 2023-12-01
    “…The result of the naïve bayes method with FD extraction on the Multinomial kernel yield the highest accuracy of 83% in light scenarios while the Bernoulli kernel provides the lowest accuracy 46% in both dark and light scenarios. Based on the comparison of the classification result of the two methods, it is suggested that the SVM method for FD extraction is more recommended in the herbal leaf classification process. …”
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    Incidence and pathological features of IgA nephropathy before and during the COVID-19 pandemic by Wen Liu, Ricong Xu, Di Wu, Zhihang Su, Yuan Cheng, Haofei Hu, Xinzhou Zhang, Qijun Wan

    Published 2025-02-01
    “…The study focused on variations in the incidence of IgAN, and collected clinical and pathological data to assess pathological changes using the Oxford Classification (MEST-C). The findings revealed a significant increase in the incidence of IgAN during the COVID-19 pandemic, from 39.9% prior to the pandemic to 46.3% during it, representing a net increase of 6.4% (P < 0.001). …”
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    Incidence and risk factors for mortality of vertebral osteomyelitis: a retrospective analysis using the Japanese diagnosis procedure combination database by Hideo Yasunaga, Hirotaka Chikuda, Kiyohide Fushimi, Hiromasa Horiguchi, Toru Akiyama, Kazuo Saita

    Published 2013-03-01
    “…Objective To examine the incidence of vertebral osteomyelitis (VO) and the clinical features of VO focusing on risk factors for death using a Japanese nationwide administrative database.Design Retrospective observational study.Setting Hospitals adopting the Diagnosis Procedure Combination system during 2007–2010.Participants We identified 7118 patients who were diagnosed with VO (International Classification of Diseases, 10th Revision codes: A18.0, M46.4, M46.5, M46.8, M46.9, M48.9 and M49.3, checked with the detailed diagnoses in each case and all other codes indicating the presence of a specific infection) and hospitalised between July and December, 2007–2010, using the Japanese Diagnosis Procedure Combination database.Main outcome measures The annual incidence of VO was estimated. …”
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    Characteristic analysis and surgical exploration for acetabular roof fractures: Multicenter retrospective cohort study. by Ruipeng Zhang, Yingchao Yin, Wei Chen, Yan Zhuang, Shicai Fan, Chengla Yi, Gang Lyu, Longpo Zheng, Xiaodong Guo, Ming Li, Guangyao Liu, Zhiyong Hou, Yingze Zhang

    Published 2025-01-01
    “…<h4>Background</h4>Acetabular roof was a crucial structure for maintaining the stability of hip joint; however, its important role was not especially emphasized in the Letournel-Judet classification system. Acetabular roof was segmented into the roof column and roof wall in Three-column classification and fracture in this area alone was defined as A3 injury. …”
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    Evaluasi Kinerja MLLIB APACHE SPARK pada Klasifikasi Berita Palsu dalam Bahasa Indonesia by Antonius Angga Kurniawan, Metty Mustikasari

    Published 2022-06-01
    “…Hasil menunjukkan bahwa MLlib Apache Spark terbukti memiliki kinerja yang cepat dan baik karena dalam melakukan pemrosesan machine learning, running time tercepat yang didapat adalah 6.46 detik dengan menggunakan algoritma Logistic Regression. …”
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    Analisis Sentimen untuk Identifikasi Bantuan Korban Bencana Alam berdasarkan Data di Twitter Menggunakan Metode K-Means dan Naive Bayes by Vincentius Riandaru Prasetyo, Gatum Erlangga, Delta Ardy Prima

    Published 2023-10-01
    “…The K-Means method was chosen because it is easy to use and easy to implement, while the Naïve Bayes method was chosen because it has a good level of accuracy in classification. The results showed that the combination of K-Means and Naïve Bayes had a higher accuracy rate of 76.46%, compared to the use of Naïve Bayes alone, which was 74.65%. …”
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    Deteksi Gulma Berdasarkan Warna HSV dan Fitur Bentuk Menggunakan Jaringan Syaraf Tiruan by Hurriyatul Fitriyah, Rizal Maulana

    Published 2021-10-01
    “…The testing on the weed classification in a real outdoor environment showed 95.46% accuracy using a total of 149 detected plants (70% as training data, 15%  as validation data, and 15% as testing data). …”
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