Deep learning-based segmentation of small-volume brain metastases in lung cancer patients
April 2026
Brain metastases from lung cancer typically present as multiple small lesions, creating considerable challenges for accurate segmentation. While existing datasets and models have primarily focused on...
AI-based diagnosis of clear-cell renal cell carcinoma based on non-contrast CT
April 2026
The accurate characterization of renal tumors, particularly clear-cell renal cell carcinoma (ccRCC), traditionally requires contrast-enhanced computed tomography (CECT), which is contraindicated in...
A multiscale residual dense fusion network for nuclear medical image fusion
Available online 2 April 2026
Multimodal medical image fusion technology generates new images containing more accurate disease information by fusing different modal images. It not only improves the accuracy and efficiency of diagnosis...
Integrative machine learning-driven prioritization of ceRNA networks in adrenocortical carcinoma
Available online 2 April 2026
Adrenocortical carcinoma (ACC) is a rare and highly aggressive endocrine malignancy in urgent need of robust biomarkers and novel therapeutic targets. In this study, a machine learning-driven framework...
Analysis of key technologies and intelligent development trends for a tumor surgery navigation platform
Available online 2 April 2026
With the rapid development of artificial intelligence (AI) and multimodal imaging technology, intelligent surgical navigation systems have become a research hotspot in the field of precision tumor treatment....
Advancing Precision Oncology Through hNQO1-Activatable NIR-II Probes: Integrating Molecular Imaging with Artificial Intelligence
Available online 1 April 2026
Traditional imaging modalities often lack the molecular specificity and spatial resolution required for real-time tumor visualization, particularly in complex surgical settings. This narrative review...
From morphology to function: Advances in multimodal imaging for pulmonary function prediction and the emerging concept of radiophenomics
Available online 25 March 2026
Pulmonary function testing is a vital noninvasive method for evaluating respiratory system function and is widely used in the diagnosis, surgical risk assessment, and prognostic prediction of chronic...
Integrating multi-omic liquid biopsies and artificial intelligence: The next frontier in early cancer detection
January 2026
The integration of multi-omic liquid biopsies with artificial intelligence (AI) represents a rapidly evolving frontier in early cancer detection, offering the potential to enhance personalized medicine...
Predicting the effectiveness of neoadjuvant therapy in rectal cancer patients: Model construction based on radiomics and carcinoembryonic antigens
January 2026
This study aimed to develop a multimodal imaging histological model based on computed tomography (CT) images and carcinoembryonic antigen (CEA) values to predict the efficacy of preoperative neoadjuvant...
Multimodal medical imaging AI for breast cancer diagnosis: A comprehensive review
January 2026
Traditional artificial intelligence (AI)-based methods for breast cancer diagnosis often rely on a single modality, such as ultrasound images. With the rise of multimodal approaches, multiple data sources,...
Integrative multi-omics clustering for identifying novel breast cancer subtypes with distinct molecular and clinical characteristics
January 2026
As a heterogeneous disease, breast cancer requires refined classification frameworks that can effectively guide targeted therapies. However, traditional methods fail to capture the comprehensive molecular...
Harnessing computational power for intelligent oncology in the age of large models: Status, challenges, and prospects
January 2026
The integration of large-scale foundation models (e.g., GPT series and AlphaFold) into oncology is fundamentally transforming both research methodologies and clinical practices, driven by unprecedented...
Decision-making performance of large language models vs. human physicians in challenging lung cancer cases: A real-world case-based study
January 2026
Despite the promise shown by large language models (LLMs) for standardized tasks, their multidimensional performance in real-world oncology decision-making remains unevaluated. This study aims to introduce...
Deep learning in abdominal organ segmentation: A review
October 2025
Abdominal organ segmentation is an essential and fundamental medical procedure with many clinical and research applications. There is extensive variability in the size, location, and shape of the abdominal...
Virtual cells in intelligent oncology
October 2025
Artificial intelligence in surgical oncology: A comprehensive review from preoperative planning to postoperative care
October 2025
While artificial intelligence (AI) has demonstrated significant potential across medical fields, its surgical applications, particularly in oncology remain largely exploratory. This review synthesizes...
A depth-wise separable residual neural network for PCDH8 status prediction in thyroid cancer pathological images
October 2025
Accurate prediction of protocadherin 8 (PCDH8) gene expression status from whole-slide images (WSIs) is critical for thyroid cancer diagnosis and prognosis, as PCDH8 overexpression is associated with...
Deep learning-based localization of preoperative parathyroid glands in secondary hyperparathyroidism patients using dual-phase unenhanced and contrast-enhanced computed tomography data
October 2025
Accurate preoperative localization of parathyroid glands (PGs) is crucial for patients with secondary hyperparathyroidism scheduled for parathyroidectomy. However, despite its importance, localization...
Medical multimodal large language models: A systematic review
October 2025
The rapid advancement of artificial intelligence (AI) has ushered in a new era of medical multimodal large language models (MLLMs), which integrate diverse data modalities such as text, imaging, physiological...
Graph attention network enables multipurpose prediction of imaging mass cytometry in a hepatocellular carcinoma clinical trial
October 2025
Imaging mass cytometry (IMC) enables the high-resolution spatial profiling of tumor microenvironment, but its clinical utility for prospective prediction remains underdeveloped. In this study, we integrated...
Performance evaluation of artificial intelligence–assisted diagnostic tools for human papillomavirus–related cervical and anal cancers and their precancerous lesions: A systematic review and meta-analysis
October 2025
Detection of high-grade squamous intraepithelial lesions (HSILs) is key for the prevention of human papillomavirus (HPV)–related cancers. In this study, we aimed to identify and consolidate the existing...
A narrative review of the prediction of immunotherapy efficacy for treating NSCLC: An artificial intelligence perspective
July 2025
Immunotherapy efficacy in non-small cell lung cancer (NSCLC) remains variable, with traditional biomarkers (programmed death-ligand 1 [PD-L1] and tumor mutational burden) limited by heterogeneity and...