Traditional pulmonary function tests (PFTs) are indispensable but have well‑known blind spots: reliance on patient cooperation, lack of regional information, and inability to detect early structural changes. A new review in Intelligent Oncology (Volume 2, Issue 2, 2026) discusses how multimodal imaging (X‑ray, CT, MRI, nuclear medicine) combined with radiomics and deep learning can predict pulmonary function. It highlights the shift from traditional PFTs (limited by patient cooperation, lack of regional data, and insensitivity to early lesions) to imaging‑based models that quantify emphysema, airway remodeling, ventilation‑perfusion mismatch, and even lobar‑level functional contribution. The article also introduces the novel concept of “lung biological age” — using imaging features to assess how an individual’s lung function deviates from age‑matched norms.

Tumor surgery faces challenges such as unclear lesion boundaries, complex anatomy, and intraoperative tissue deformation. Traditional navigation systems struggle with soft‑tissue dynamics and real‑time accuracy. A new review published in Intelligent Oncology examines how AI and multimodal imaging are driving next‑generation surgical navigation toward greater precision and safety.

In a new editorial published in Intelligent Oncology, the journal’s editor-in-chief, Professor Bo Xu, presents a compelling vision for the future of cancer research: artificial intelligence (AI) as a unifying, quantitative “meta-lens” that transforms the multidimensional hallmarks of cancer into clinically actionable insights.