Comparison and summary of the AI-based model CNN with radiology imaging results
| Category | Radiologist 1 | Radiologist 2 | Radiologist 3 | EfficientNet B0 (AI) | Pooled radiologist finding | Proposed AI model CNN finding |
|---|---|---|---|---|---|---|
| Total cases with nodules | 100 | 100 | 100 | 100 | - | - |
| Benign nodules | 73 | 70 | 65 | 72 | 69.3% | 72% |
| Malignant nodules | 22 | 25 | 20 | 28 | 22.3% | 28% |
| Suspicious cases | 5 | 5 | 15 | 0 | 8.4% | 0 |
AI: artificial intelligence; CNN: convolutional neural network; -: not applicable
We acknowledge the support and facilities provided by our institution for conducting this research. We also extend our gratitude to all faculty members and staff who contributed to data collection and analysis. We are especially grateful to the Multidisciplinary Research Unit (MRU—a unit of the Department of Health Research) for their continued support throughout the research process, up to the submission of this manuscript.
AKA: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing—original draft, Writing—review & editing. PB: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing—original draft, Writing—review & editing. AR: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing—original draft, Writing—review & editing. KS: Conceptualization, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing—original draft, Writing—review & editing. All authors read and approved the submitted version.
The authors declare that they have no conflicts of interest.
Ethical approval for this study was obtained from the Institutional Ethics Committee Review Board of Madras Medical College, Chennai (Ec.No.02122021).
The need for informed consent was waived for this retrospective review of patient records, imaging data, and biomaterials. All CT data and pathological specimens were provided by the host institution.
Not applicable.
The proposed BIR Lung Dataset in the article, version 1 data is available online with the following link https://doi.org/10.34740/KAGGLE/DSV/8288306.
Not applicable.
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