Other Cancers

CT-based radiomics for predicting the treatment response to PD-1/PD-L1 inhibitors combined with chemotherapy in unresectable gastric cancer.

OBJECTIVE: To develop and validate a CT-based radiomics model to predict immunotherapy response in unresectable gastric cancer and explore its underlying biological mechanisms. MATERIALS AND METHODS: This retrospective study included 368 unresectable gastric cancer patients receiving programmed death-1/programmed death ligand-1 (PD-1/PD-L1) inhibitors combined with chemotherapy from two centers. P...

Artificial intelligence for diagnosis and triage in oral cancer: a clinician‑centered narrative review.

BACKGROUND: Early diagnosis of oral squamous cell carcinoma (OSCC) remains challenging, with survival largely stage-dependent at presentation. Artificial intelligence (AI) promises to enhance detection and clinical decision-making across clinical photographs, radiology, optical imaging, and digital pathology. METHODS: This narrative review synthesizes peer-reviewed PubMed-indexed English-language ...

Initial experience of deep learning reconstruction algorithm in lung kernel: clinical usefulness for lung nodules at ultra-low-dose protocol.

OBJECTIVES: TrueFidelity (TF), a deep learning image reconstruction algorithm that was originally available only in standard kernel, has recently beco...

A lactylation-related gene signature predicts prognosis and immunotherapy response in clear cell renal cell carcinoma based on machine learning and multi-omics analysis.

CT Radiomics-Based Machine Learning Model for Predicting Capsular and Neural Invasion in Thyroid Carcinoma: Diagnostic Accuracy Study.

BACKGROUND: Thyroid carcinoma is the most prevalent endocrine malignancy, with a worldwide increasing incidence. Capsular invasion and neural invasion...

Evaluating the ability of generative AI to standardize TNM staging data in lung cancer.

This study evaluates the ability of generative artificial intelligence (AI) models to standardize tumor-node-metastasis (TNM) staging data in lung can...

TRIM36 and CAMK2N2 regulate ferroptosis and antigen presentation in small cell lung cancer.

Small cell lung cancer (SCLC) is a highly aggressive tumor with poor prognosis. Ferroptosis is closely linked to tumor antigen presentation: it affect...

Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation study.

BACKGROUND: Genomic assays such as Oncotype DX have transformed adjuvant treatment selection for hormone receptor-positive, HER2-negative, early breas...

Accelerated discovery of cell migration regulators using label-free deep learning-based automated tracking.

Cell migration underlies immune surveillance, tissue repair, embryogenesis, and-when dysregulated-tumor metastasis. Yet unlike proliferation, which ca...

Integrative analysis of mRNA stability regulation uncovers a metastasis-suppressive program in breast cancer.

Heterogeneity in cancer gene expression is typically linked to genetic and epigenetic alterations, yet the extent of contribution from posttranscripti...

SMC-LUD:Large-Scale B-Mode Liver Ultrasound Dataset for Hepatocellular Carcinoma and Hemangioma Classification.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality globally, and accurate classification of liver lesions using ultrasound ...

Development of head-to-head and longitudinal CycleGAN algorithm for MRI harmonization: validation in follow-up MRI evaluation in patients with brain metastasis.

Various harmonization methods have been employed for obtaining MRI from different scanners. However, no study has yet focused on the clinical utility ...

Artificial intelligence-assisted spatial omics-based biomimetic nanoplatform for intelligent and precise intervention in the immunosuppressive core region of ovarian cancer.

Ovarian cancer (OC) ranks among the most aggressive malignancies of the female reproductive system. The immunosuppressive tumor microenvironment (TME)...

Design of an optimal planning framework for cryosurgical treatment of brain tumor using CNN segmentation of MRI images.

This study presents an integrated methodology for pre-operative cryosurgical planning of irregularly shaped brain tumors using two-dimensional MRI dat...

[Application of artificial intelligence in pathological diagnosis of ocular tumors].

Ocular tumors encompass ocular surface tumors, orbital tumors, and intraocular tumors, characterized by high heterogeneity and complex classifications...

Targeting metabolism to combat anticancer and antibacterial drug resistance.

Drug resistance is a major challenge in cancer and infectious diseases, requiring innovative solutions. Recent research suggests that bacteria and can...

Towards long-term sleep staging via wearable reflective photoplethysmography.

STUDY OBJECTIVES: Sleep staging is usually performed by manual scoring of polysomnography (PSG), which is expensive, laborious, and poorly scalable. W...

DeepStackVEGF a stacking ensemble deep learning framework for vascular endothelial growth factor prediction.

Vascular Endothelial Growth Factor (VEGF) plays a central role in angiogenesis, regulating both physiological processes such as wound healing, tissue ...

BRAF inhibitor resistance in melanoma: from resistance mechanisms to therapeutic innovations.

BRAF inhibitors (BRAFi) have transformed the treatment of BRAF mutant melanoma, but inherent and acquired resistance remains a major barrier to curati...

Computer-aided diagnosis of papillary thyroid carcinoma based on deep learning technology.

This article examines global thyroid cancer（TC） incidence trends, with emphasis on epidemiological patterns in China, where papillary thyroid carcinom...