The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Deep Learning in Medical Image Analysis
Open accessAbstract
Deep learning is the state-of-the-art machine learning approach. The success of deep learning in many pattern recognition applications have brought excitement and high expectations that deep learning, or artificial intelligence (AI), can bring revolutionary changes in health care. Early studies of deep learning applied to lesion detection or classification have reported superior performance compared to those by conventional techniques or even better than radiologists in some tasks. The potential of applying deep-learning-based medical image analysis to computer-aided diagnosis (CAD), thus providing decision support to clinicians and improving the accuracy and efficiency of various diagnostic and treatment processes, has spurred new research and development efforts in CAD. Despite the optimism in this new era of machine learning, the development and implementation of CAD or AI tools in clinical practice face many challenges. In this chapter, we will discuss some of these issues and efforts needed to develop robust deep-learning-based CAD tools and integrate these tools into the clinical workflow, thereby advancing towards the goal of providing reliable intelligent aids for patient care.
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Cites
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Cited by
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“In deep learning models the features can be learnt automatically [6].”
BackgroundMethodInfluentialAI in Medical Education: Global situation, effects and challenges
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Metadata
- Authors
- Chan, H.-P., Samala, R. K., Hadjiiski, L. M., & Zhou, C.
- Venue
- Advances in Experimental Medicine and Biology
- Publisher
- Springer International Publishing
- Published
- 2020
- Volume
- 1213
- Pages
- 3-21
- ISSN
- 0065-2598 (ISSN-L)
- 2214-8019
- OpenAlex
- W3004868960
- Cited by
- 747
- References
- 66
- FWCI
- 129.20
- Type
- book chapter
- Language
- en
- Open access
- green
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- Chan, H.-P., Samala, R. K., Hadjiiski, L. M., & Zhou, C. (2020). Deep Learning in Medical Image Analysis. Advances in Experimental Medicine and Biology. https://doi.org/10.1007/978-3-030-33128-3_1
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