AI-driven Characterization of Solid Pulmonary Nodules on CT Imaging for Enhanced Malignancy Prediction in Small-sized Lung Adenocarcinoma.
Yujin KudoTaiyo NakamuraJun MatsubayashiAkimichi IchinoseYushi GotoRyosuke AmemiyaJinho ParkYoshihisa ShimadaMasatoshi KakihanaToshitaka NagaoTatsuo OhiraJun MasumotoNorihiko IkedaPublished in: Clinical lung cancer (2024)
In small-sized lung cancer diagnosed as cN0, AI automatically identifies tumors as solid nodules ≤2 cm and evaluates their malignancy preoperatively. The AI classification can inform lymph node assessment necessity in sublobar resections, reflecting metastatic potential.
Keyphrases
- artificial intelligence
- lymph node
- machine learning
- deep learning
- small cell lung cancer
- squamous cell carcinoma
- high resolution
- pulmonary hypertension
- computed tomography
- lymph node metastasis
- neoadjuvant chemotherapy
- image quality
- dual energy
- gene expression
- dna methylation
- risk assessment
- magnetic resonance
- early stage
- photodynamic therapy
- rectal cancer