ArticleJournal of personalized medicine2024
Can Artificial Intelligence Replace Humans for Detecting Lung Tumors on Radiographs? An Examination of Resected Malignant Lung Tumors.
Article in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Article
- Evaluation of large language models in a pulmonology outpatient clinic using structured clinical data and chest radiographs: a single-center prospective observational study.Frontiers in medicine · 2026Article
- Assessment of AI software's diagnostic accuracy in identifying impacted teeth in panoramic radiographs.European journal of orthodontics · 2025Article
- Diagnostic accuracy of an artificial intelligence-based software in detecting supernumerary and congenitally missing teeth in panoramic radiographs.European journal of orthodontics · 2025Article
- A Holistic Approach to Implementing Artificial Intelligence in Lung Cancer.Indian journal of surgical oncology · 2025Review
- A Systematic Review: The Role of Artificial Intelligence in Lung Cancer Screening in Detecting Lung Nodules on Chest X-Rays.Diagnostics (Basel, Switzerland) · 2025Review
- Effectiveness of artificial intelligence for detecting operable lung cancer on chest radiographs.Translational lung cancer research · 2024Article
- Role of artificial intelligence (Google bard) in morphological, histopathological, and radiological image identifications: Objective Structured Practical Examination (OSPE) type-based performance.Saudi medical journal · 2024Article
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2 authors.
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Abstract
objectiveAlthough lung cancer screening trials have showed the efficacy of computed tomography to decrease mortality compared with chest radiography, the two are widely taken as different kinds of clinical practices. Artificial intelligence can improve outcomes by detecting lung tumors in chest radiographs. Currently, artificial intelligence is used as an aid for physicians to interpret radiograms, but with the future evolution of artificial intelligence, it may become a modality that replaces physicians. Therefore, in this study, we investigated the current situation of lung cancer diagnosis by artificial intelligence.
methodsIn total, we recruited 174 consecutive patients with malignant pulmonary tumors who underwent surgery after chest radiography that was checked by artificial intelligence before surgery. Artificial intelligence diagnoses were performed using the medical image analysis software EIRL X-ray Lung Nodule version 1.12, (LPIXEL Inc., Tokyo, Japan).
resultsThe artificial intelligence determined pulmonary tumors in 90 cases (51.7% for all patients and 57.7% excluding 18 patients with adenocarcinoma in situ). There was no significant difference in the detection rate by the artificial intelligence among histological types. All eighteen cases of adenocarcinoma in situ were not detected by either the artificial intelligence or the physicians. In a univariate analysis, the artificial intelligence could detect cases with larger histopathological tumor size (
conclusionsOur study showed that using artificial intelligence, the diagnosis of tumor-associated findings and the diagnosis of areas that overlap with anatomical structures is not satisfactory. While the current standing of artificial intelligence diagnostics is to assist physicians in making diagnoses, there is the possibility that artificial intelligence can substitute for humans in the future. However, artificial intelligence should be used in the future as an enhancement, to aid physicians in the role of a radiologist in the workflow.
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