Automated Lung Auscultation Identification for Mobile Health Systems Using Machine Learning

被引：0
|
作者：
Lindsey Serato, Jo Hanna [1 ]
Reyes, Rosula [1 ]
机构：
[1] Ateneo Manila Univ, Katipunan Ave, Quezon City, Metro Manila, Philippines
来源：
PROCEEDINGS OF 4TH IEEE INTERNATIONAL CONFERENCE ON APPLIED SYSTEM INNOVATION 2018 ( IEEE ICASI 2018 ) | 2018年
关键词：
classification algorithm; KNN; SVM; auscultation; predictive analysis;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
An efficient classification system that aids in the computerized auscultation process was developed. A database of digital lung sounds was created from recorded lung sounds from anonymous patients using mobile application and digital stethoscopes. Efficiency of different classification algorithms to the dataset was tested, and their processing time was reduced up to 80.15% when applied with Principal Component Analysis (PCA). Among the six classification algorithms used, K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) are more reliable to use in this dataset with a precision of 100% and 99.00%, respectively.
引用
收藏
页码：287 / 290
页数：4
相关论文
共 50 条
  • [21] Human identification in health care systems using mobile edge computing
    Yu, Wenjun
    Choi, Jaeho
    TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2020, 31 (12):
  • [22] Automated classification of building structures for urban built environment identification using machine learning
    Zhou, Peng
    Chang, Yuan
    JOURNAL OF BUILDING ENGINEERING, 2021, 43
  • [23] Assessment of Automated Identification of Phases in Videos of Cataract Surgery Using Machine Learning and Deep Learning Techniques
    Yu, Felix
    Croso, Gianluca Silva
    Kim, Tae Soo
    Song, Ziang
    Parker, Felix
    Hager, Gregory D.
    Reiter, Austin
    Vedula, S. Swaroop
    Ali, Haider
    Sikder, Shameema
    JAMA NETWORK OPEN, 2019, 2 (04) : e191860
  • [24] Automated Identification of DICOM-RT Structures Using Map Projections and Machine Learning
    Cutright, D.
    Wu, T.
    Roy, A.
    Gopalakrishnan, M.
    Mittal, B.
    MEDICAL PHYSICS, 2020, 47 (06) : E583 - E583
  • [25] Prediction and identification of nonlinear dynamical systems using machine learning approaches
    Jin, Leisheng
    Liu, Zhuo
    Li, Lijie
    JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 2023, 35
  • [26] System Identification and Process Modelling of Dynamic Systems Using Machine Learning
    Inapakurthi, Ravi Kiran
    Mitra, Kishalay
    2022 26TH INTERNATIONAL CONFERENCE ON SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC), 2022, : 564 - 569
  • [27] Driver identification in intelligent vehicle systems using machine learning algorithms
    Li, Zhengping
    Zhang, Kai
    Chen, Bokui
    Dong, Yuhan
    Zhang, Lin
    IET INTELLIGENT TRANSPORT SYSTEMS, 2019, 13 (01) : 40 - 47
  • [28] Categorization of spam images and identification of controversial images on mobile phones using machine learning and predictive learning
    Jain, Vanita
    Kapoor, Rishabh
    Gulyani, Shashwat
    Dubey, Arun Kumar
    JOURNAL OF DISCRETE MATHEMATICAL SCIENCES & CRYPTOGRAPHY, 2019, 22 (02): : 293 - 307
  • [29] Real-Time Application Identification Method for Mobile Networks Using Machine Learning
    Ou, Tatsuhiro
    Nakao, Akihiro
    PROCEEDINGS OF 2024 IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM, NOMS 2024, 2024,
  • [30] Automated ReaxFF parametrization using machine learning
    Daksha, Chaitanya M.
    Yeon, Jejoon
    Chowdhury, Sanjib C.
    Gillespie, John W.
    Computational Materials Science, 2021, 187
12345