Other Cancers

OpenIO: An open framework for AI-native immunotherapy.

We propose Open Immune Oncology (OpenIO), a framework integrating generative AI and omics to advance precision oncology. By leveraging biological scaling laws and foundation models, we aim to transition immunotherapy from empirical screening to rational, AI-native engineering of therapeutic interventions.

[An auxiliary diagnosis system for cervical intraepithelial neoplasia based on colposcopic images].

Cervical intraepithelial neoplasia is the primary type of cervical precancerous lesion; however, manual clinical diagnosis is prone to bias and has limited grading accuracy. To achieve precise automated grading of CIN, this paper proposes a multimodal fusion Swin Transformer model and develops a corresponding computer-aided diagnosis system. This method employs three-channel fusion of raw images, ...

Integrating machine learning with histopathological, immunohistochemical, and PET parameters in the study of invasive breast carcinoma, no special type.

BACKGROUND: This study investigates the relationship between histopathological (HP) features, immunohistochemical (IHC) markers, 18F- FDG PET/CT param...

Review Article: Advances in the Diagnosis of Dysplasia in Barrett's Oesophagus.

BACKGROUND: Barrett's oesophagus (BE), the precursor to oesophageal adenocarcinoma, progresses through a stepwise dysplastic sequence. Accurate dyspla...

Tumor organoid platform design for drug response modeling: culture architecture, microenvironmental complexity, and AI-assisted readouts.

Tumor organoids preserve the cellular heterogeneity and structural complexity of native tumors, providing robust platforms for mechanistic studies, pr...

Heterogeneity Analyzed by CT-Based Habitat Analysis for Clinical Management of Cancers: A Narrative Review.

Tumors are highly heterogeneous, and whole-lesion radiomics analysis is a popular method for extracting texture features that reflect this heterogenei...

AI-driven discovery of GPNMB CAR T cells as a multi-cancer therapy.

Chimeric antigen receptor (CAR) T cells have demonstrated curative potential in hematologic cancers and increasing efficacy in solid tumors and non-ma...

Development of a LASSO-based machine learning model for relapse prediction in lupus nephritis.

OBJECTIVE: To identify the predictors of renal relapse in patients with lupus nephritis (LN) and develop a predictive model. METHODS: The patients wit...

Value operating system: a practical framework to measure outcomes-per-cost at the episode level.

OBJECTIVE: To specify a value operating system (VOS) and its executable metric-the Value Index (VI)-that expresses risk-adjusted outcomes-per-episode-...

Prediction of cardiac arrest in patients with heart failure in Sweden: a registry study with development of a machine learning model.

OBJECTIVE: 30-day survival after cardiac arrest is low, 12.4% and 36% for out-of-hospital and in-hospital cardiac arrest, respectively. Heart failure ...

IL4Rα blockade inhibits proliferation of malignant lymphocytes and the immunosuppressive tumor microenvironment of mycosis fungoides.

BACKGROUND: Limited therapeutic options are available for patients with advanced-stage mycosis fungoides (MF), and the 5-year survival rate is 25%. Du...

Diagnosis of Small Focal Liver Lesions (≤2 cm): A Deep Learning Approach Based on B-Mode Ultrasound and Contrast-Enhanced Ultrasound.

BACKGROUND: To develop and validate a deep learning (DL) model based on feature fusion with B-mode ultrasound (BMUS) and contrast enhanced ultrasound ...

Oral cancer in the era of precision medicine: molecular targets and technological innovations.

This topical Collection presents a series of studies that examine molecular mechanisms, diagnostic approaches, and therapeutic strategies relevant to ...

A prediction model based on tumor immune microenvironment for immunotherapy response in gastric cancer.

This study aimed to develop a robust prediction model- using machine-learning algorithms based on the core indicators of the tumor immune microenviron...

Metabolic determinants of cancer immunotherapy outcomes identified by plasma profiling.

Immune-checkpoint inhibitors benefit a subset of patients with advanced cancer, and the metabolic determinants of response remain unclear. Here, using...

A bibliometric analysis of research trends and future directions in early detection of pancreatic cancer.

BACKGROUND: Research on the early detection of pancreatic cancer has grown rapidly in recent years; however, existing bibliometric studies in this fie...

Mapping the research landscape of myelodysplastic syndromes: a scientometric analysis (2014-2025).

This scientometric study critically evaluates the global evolution of myelodysplastic syndromes (MDS) research from 2014 to 2025, aiming to integrate ...

Deep learning-driven MRI radiomics reveals biological subtypes and predicts recurrence risk in rectal cancer.

Traditional TNM staging inadequately captures the recurrence risk of rectal cancer (RC), limiting prognostic accuracy and personalized treatment decis...

Feasibility of deep learning-accelerated ultrafast T1-weighted VIBE Dixon imaging of the pelvis for screening of metastases in prostate MRI.

OBJECTIVE: This study aims to assess the image quality and perceived diagnostic confidence of research deep learning (DL)-accelerated T1-weighted "vol...

Oral squamous cell carcinoma diagnosis: an interpretable deep learning approach using multi-scale pathological images.

BACKGROUND: Diagnosis of oral squamous cell carcinoma (OSCC) currently relies heavily on the subjective experience of pathologists. This process is ti...