Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : joiv international journal on informatics visualization

Tree-based Filtering in Pulse-Line Intersection Method Outputs for An Outlier-tolerant Data Processing Damarjati, Cahya; Trinanda Putra, Karisma; Wijayanto, Heri; Chen, Hsing-Chung; Nugraha, Toha Ardi
JOIV : International Journal on Informatics Visualization Vol 6, No 1 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1.861

Abstract

Pulse palpation is one of the non-invasive patient observations that identify patient conditions based on the shape of the human pulse. The observations have been practiced by Traditional Chinese Medicine (TCM) practitioners since thousands of years ago. The practitioners measure the patient’s arterial pulses in three points of both patient wrists called chun, guan, and chy, then diagnose based on their knowledge and experience. Pulse-Line Intersection (PLI) method extract features of each pulse from the observed pulse wave sequence. PLI is performed by summing the number of intersections between the artificial line and the pulse wave. The method is proven in differentiating between hesitant with moderate pulse waves. As the method implemented in Clinical Decision Support System (CDSS) related to pulse palpation, some outlier data might emerge and affect the measurement result. Thus, outlier filtering is needed to prevent unnecessary prediction processes by machine learning (ML) models inside CDSS. This study proposed an outlier filtering model using a decision tree algorithm. This concept is designed by analyzing pulse features values and the chance of odd values combination. Then inappropriate values are excepted using several rules. Every pulse feature list that did not pass the filtering rule is categorized as outliers and were not included for further process. The proposed model works more efficiently than ML models dealing with outliers since this procedure is unsupervised learning with a small number of parameters. Overall, the proposed filtering method can be used in pulse measurement applications by eliminating outlier data that might decrease the performance of ML models.
Co-Authors Abdul Eriawan Nahar Abdurrahim, Minhajuddin K. Abyiyansyah Meidy Laksono Adhianty Nurjanah Ahmad Musthafa Masyhur Amelia Mutiara Ayu Ratiwi Andhika Putra Setianto Aprilia Kurnianti Aprilia Kurniati, Aprilia Arifia Kasastra R ARIS NUGROHO Asnor Juraiza Ishak Asri Tri Wulandari Asroni Asroni Asroni Asroni Asroni Asroni Asroni, Asroni Ayu Ratiwi, Amelia Mutiara Azizah, Laila Marifatul Bahrurozi, Sofran Chen, Hsing-Chung Dede Chandra Dimas Bagas Ajipratama Edifianto, Gilang Hendra Dita Eko Fajar Cahyadi Eko Prasetyo Fadhan Anwarodin Fauri Hakim Gilang Hendra Dita Edifianto Heri Wijayanto Hsing-Chung Chen Indira Prabasari Indira Prabasari, Indira Irawan, Ricki Ishak, Asnor Juraiza Kamarul Hawari Ghazali Karim, Rohana Abdul Karisma Trinanda Putra, Karisma Trinanda Kasastra R, Arifia Laila Ma’rifatul Azizah Lukito Edi Nugroho Mahardika, Naufal Gita Mahmudi, Muhammad Nazih Masyhur, Ahmad Musthafa Maududi Nur Imani Tarigan Minhajuddin K. Abdurrahim Muhamad Arief Previasakti Suradi Muhammad Alfadha Termahadi Muhammad Dzaki Mubarok Mukhtar Hanafi Musyary, Musyary Nafi Ananda Utama Nano Prawoto Nasrul Saefullah Nisrina Akbar Rizky Putri Prasetyo, Satria Prayitno Prayitno Ramli, Suzaimah Ricki Irawan Ridho Al-Hamdi Rochmah, Faizatur Salsabila, Lathifah Khansa Sartika Puspita Setianto, Andhika Putra Sifa Dinia Silvester Tena Siti Khotimah Slamet Handoko Slamet Riyadi Slamet Riyadi Slamet Riyadi Sofiani, Erma Sofran Bahrurozi Sri Suning Kusumawardani Sunardi Sunardi Suparman Suradi, Muhamad Arief Previasakti Suwadi Suwadi Titis Wisnu Wijaya Titis Toha Ardi Nugraha Tony K Hariadi Trinanda Putra, Karisma Triyani, Wahyu Indah Utama, Nafi Ananda Yunita Lestari