IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v145y2021ics0960077921001028.html
   My bibliography  Save this article

Using handpicked features in conjunction with ResNet-50 for improved detection of COVID-19 from chest X-ray images

Author

Listed:
  • Rajpal, Sheetal
  • Lakhyani, Navin
  • Singh, Ayush Kumar
  • Kohli, Rishav
  • Kumar, Naveen

Abstract

Coronaviruses are a family of viruses that majorly cause respiratory disorders in humans. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new strain of coronavirus that causes the coronavirus disease 2019 (COVID-19). WHO has identified COVID-19 as a pandemic as it has spread across the globe due to its highly contagious nature. For early diagnosis of COVID-19, the reverse transcription-polymerase chain reaction (RT-PCR) test is commonly done. However, it suffers from a high false-negative rate of up to 67% if the test is done during the first five days of exposure. As an alternative, research on the efficacy of deep learning techniques employed in the identification of COVID-19 disease using chest X-ray images is intensely pursued.

Suggested Citation

  • Rajpal, Sheetal & Lakhyani, Navin & Singh, Ayush Kumar & Kohli, Rishav & Kumar, Naveen, 2021. "Using handpicked features in conjunction with ResNet-50 for improved detection of COVID-19 from chest X-ray images," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    • Handle: RePEc:eee:chsofr:v:145:y:2021:i:c:s0960077921001028
    DOI: 10.1016/j.chaos.2021.110749
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921001028
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2021.110749?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Altan, Aytaç & Karasu, Seçkin, 2020. "Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning technique," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Karasu, Seçkin & Altan, Aytaç & Bekiros, Stelios & Ahmad, Wasim, 2020. "A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series," Energy, Elsevier, vol. 212(C).
    3. Altan, Aytaç & Karasu, Seçkin & Bekiros, Stelios, 2019. "Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 325-336.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiachen Yang & Shukun Ma & Yang Li & Zhuo Zhang, 2022. "Efficient Data-Driven Crop Pest Identification Based on Edge Distance-Entropy for Sustainable Agriculture," Sustainability, MDPI, vol. 14(13), pages 1-11, June.
    2. Haoxuan Yu & Izni Zahidi, 2023. "Tailings Pond Classification Based on Satellite Images and Machine Learning: An Exploration of Microsoft ML.Net," Mathematics, MDPI, vol. 11(3), pages 1-14, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Xi & Yu, Ruyi & Ullah, Sajid & Wu, Dianming & Li, Zhiqiang & Li, Qingli & Qi, Honggang & Liu, Jihui & Liu, Min & Zhang, Yundong, 2022. "A novel loss function of deep learning in wind speed forecasting," Energy, Elsevier, vol. 238(PB).
    2. Kashkynbayev, Ardak & Cao, Jinde & Suragan, Durvudkhan, 2021. "Global Lagrange stability analysis of retarded SICNNs," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    3. Yao, Qijia, 2021. "Synchronization of second-order chaotic systems with uncertainties and disturbances using fixed-time adaptive sliding mode control," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    4. Kalantari, Mahdi, 2021. "Forecasting COVID-19 pandemic using optimal singular spectrum analysis," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    5. Alam, Muntasir & Ida, Yuki & Tanimoto, Jun, 2021. "Abrupt epidemic outbreak could be well tackled by multiple pre-emptive provisions-A game approach considering structured and unstructured populations," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    6. Shabani, Masoume & Wallin, Fredrik & Dahlquist, Erik & Yan, Jinyue, 2022. "Techno-economic assessment of battery storage integrated into a grid-connected and solar-powered residential building under different battery ageing models," Applied Energy, Elsevier, vol. 318(C).
    7. Yao, Qijia & Alsaade, Fawaz W. & Al-zahrani, Mohammed S. & Jahanshahi, Hadi, 2023. "Fixed-time neural control for output-constrained synchronization of second-order chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    8. Wang, Qiubao & Han, Zikun & Zhang, Xing & Yang, Yuejuan, 2021. "Dynamics of the delay-coupled bubble system combined with the stochastic term," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    9. Yu, Xihong & Bao, Han & Chen, Mo & Bao, Bocheng, 2023. "Energy balance via memristor synapse in Morris-Lecar two-neuron network with FPGA implementation," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    10. Liu, Shuihan & Xie, Gang & Wang, Zhengzhong & Wang, Shouyang, 2024. "A secondary decomposition-ensemble framework for interval carbon price forecasting," Applied Energy, Elsevier, vol. 359(C).
    11. Barman, Dipesh & Roy, Jyotirmoy & Alrabaiah, Hussam & Panja, Prabir & Mondal, Sankar Prasad & Alam, Shariful, 2021. "Impact of predator incited fear and prey refuge in a fractional order prey predator model," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    12. Ban, Jung-Chao & Chang, Chih-Hung & Hong, Jyy-I & Wu, Yu-Liang, 2021. "Mathematical Analysis of Spread Models: From the viewpoints of Deterministic and random cases," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    13. Zhang, Boyi & Shang, Pengjian & Zhou, Qin, 2021. "The identification of fractional order systems by multiscale multivariate analysis," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    14. Ali, Hegagi Mohamed & Ameen, Ismail Gad, 2021. "Optimal control strategies of a fractional order model for Zika virus infection involving various transmissions," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    15. Singh, Harendra & Baleanu, Dumitru & Singh, Jagdev & Dutta, Hemen, 2021. "Computational study of fractional order smoking model," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    16. Chen, Xiaolu & Weng, Tongfeng & Yang, Huijie, 2023. "Synchronization of spatiotemporal chaos and reservoir computing via scalar signals," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    17. Xiang, Jianglian & Ren, Junwu & Tan, Manchun, 2022. "Stability analysis for memristor-based stochastic multi-layer neural networks with coupling disturbance," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    18. Zhu, Ping, 2021. "An equivalent analytical method to deal with cross-correlated exponential type noises in the nonlinear dynamic system," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    19. Zhang, Xiufang & Yao, Zhao & Guo, Yeye & Wang, Chunni, 2021. "Target wave in the network coupled by thermistors," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    20. Fan, Dongyan & Sun, Hai & Yao, Jun & Zhang, Kai & Yan, Xia & Sun, Zhixue, 2021. "Well production forecasting based on ARIMA-LSTM model considering manual operations," Energy, Elsevier, vol. 220(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:145:y:2021:i:c:s0960077921001028. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.