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Everything you need to know about Computed Tomography (CT) & CT Scanning

Deep Learning: AI and COVID-19 Imaging Pearls - Educational Tools | CT Scanning | CT Imaging | CT Scan Protocols - CTisus
Imaging Pearls ❯ Deep Learning ❯ AI and COVID-19

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  • Summary: AI assistance improved radiologists’ performance in distinguishing COVID-19 from pneumonia of other etiology on chest CT.
    Key Results:
    • An AI model had higher test accuracy (96% vs 85%, p <0.0010, sensitivity (95% vs 79%, p <0.0010 and specificity (96% vs 88%, p=0.002) than radiologists.
    • In an independent test set, our AI model achieved an accuracy of 87%, sensitivity of 89% and specificity of 86%.
    • With AI assistance, the radiologists achieved a higher average accuracy (90% vs 85, p=0.001)
    AI Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Etiology on Chest CT Harrison X.
    Bai HX et al.
    Radiology 2020 (in press)
  • “AI assistance improved radiologists’ performance in distinguishing COVID-19 from non-COVID pneumonia on chest CT.”
    AI Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Etiology on Chest CT Harrison X.
    Bai HX et al.
    Radiology 2020 (in press)
  • "The COVID-19 pandemic poses a number of challenges to the Artificial Intelligence (AI) Community. Among these challenges are “Can AI help track and predict the spread of the infection?”, “Can AI help in making diagnoses and prognoses?”, “Can it be used in the search for treatments and a vaccine?” and “Can it be used for social control?” This paper is an attempt to provide an early review of how AI have so far been contributing in this regard, and to note limitations, constraints, and pitfalls. These include a lack of data, too much (noisy and outlier) data, and growing tension between data privacy concerns and public health imperatives.”
    Artificial intelligence vs COVID-19: limitations, constraints and pitfalls
    Naude W
    AI Soc. 2020 Apr 28 : 1–5.
  • • Tracking and prediction
    • Diagnosis and Prognosis
    • Treatment and vaccines
    • Social control
    Artificial intelligence vs COVID-19: limitations, constraints and pitfalls
    Naude W
    AI Soc. 2020 Apr 28 : 1–5.
  • “This paper provides an early evaluation of Artificial Intelligence (AI) against COVID-19. The main areas where AI can contribute to the fight against COVID-19 are discussed. It is concluded that AI has not yet been impactful against COVID-19. Its use is hampered by a lack of data, and by too much data. Overcoming these constraints will require a careful balance between data privacy and public health, and rigorous human-AI interaction. It is unlikely that these will be addressed in time to be of much help during the present pandemic. In the meantime, extensive gathering of diagnostic data on who is infectious will be essential to save lives, train AI, and limit economic damages.”
    Artificial intelligence vs COVID-19: limitations, constraints and pitfalls
    Naude W
    AI Soc. 2020 Apr 28 : 1–5.
© 1999-2020 Elliot K. Fishman, MD, FACR. All rights reserved.