Other Cancers

A Pulmonary Ultrasound Dataset for Tumor Segmentation and Classification.

Pulmonary tumor diagnosis with ultrasound is clinically valuable yet technically challenging. Although deep learning has shown promise in supporting sonographers, progress is hindered by the lack of publicly available, high-quality annotated datasets. Given the limited clinical adoption of pulmonary ultrasound for differentiating benign and malignant tumors, publicly available datasets for AI rese...

AI-powered risk factor analysis and development of a predictive model for lymphovascular invasion in bladder urothelial carcinoma.

Although lymphovascular invasion is a major predictor of bladder urothelial carcinoma, postoperative pathological biopsy-an intrusive procedure-remains the only reliable diagnostic technique for this condition. By combining logistic regression with various machine learning techniques, this work seeks to assess its risk factors and create a non-invasive preoperative prediction model. 520 patients w...

Intensity-modulated radiotherapy alone versus concurrent chemoradiotherapy ± induction chemotherapy in older patients with low-risk stage II or T3N0M0 nasopharyngeal carcinoma.

BACKGROUND: The optimal treatment strategy for older patients with low-risk stage II or T3N0M0 nasopharyngeal carcinoma (NPC) remains undefined. This ...

Inflammatory marker-driven deep learning model for postoperative gastric cancer prognosis.

BACKGROUND: Prognostic prediction following gastric cancer surgery plays a pivotal role in postoperative management, helping to optimize therapeutic s...

Tissue identity is the dominant determinant of cross-species transferability of a porcine developmental programme.

BACKGROUND: Reproducibility and cross-species translation using the domestic pig (Sus scrofa) are limited by the lack of a standardised molecular fram...

TREM2 in glioma: Reprogramming the immune microenvironment from mechanistic understanding to clinical translation (Review).

The poor prognosis of high‑grade gliomas, such as glioblastoma, is largely driven by a notably immunosuppressive tumor microenvironment (TME), wherein...

Perioperative prediction of adnexal malignancy by an interpretable machine learning model for guiding ovarian preservation in premenopausal endometrial cancer.

BACKGROUND: Ovarian preservation in premenopausal patients with endometrial cancer remains challenging due to the potential presence of concurrent adn...

Enhancing decision-making in surgery for a large temporocorneal meningioma through an explainable human-AI collaboration: a case report.

BACKGROUND: Meningiomas, particularly large temporocorneal meningiomas, pose significant surgical challenges due to their proximity to critical brain ...

Emerging artificial intelligence advances in oncology: latest updates from the 2026 AACR annual meeting.

Advances presented at the 2026 American Association for Cancer Research (AACR) Annual Meeting highlight a shift from standalone artificial intelligenc...

Sex Hormone Receptors, HBV Integrations and Their Prognostic Predictive Value Among Hepatocellular Carcinoma Patients.

Hepatocellular carcinoma (HCC) related to hepatitis B virus (HBV) infection predominantly affects males, yet few studies have investigated the associa...

Leveraging data-driven risk-adapted surveillance strategies after disease progression in locally advanced rectal cancer.

BACKGROUND: Post-progression survival (PPS) is a critical endpoint in oncology, yet predictors of PPS and data-driven strategies for post-progression ...

Label-free cervical cancer detection in tissue samples using Raman spectroscopy combined with machine learning technology.

Cervical cancer is one of the most common malignant tumors of the female reproductive tract, ranking fourth among all female malignancies. Currently, ...

The application of artificial intelligence in adrenal imaging: current state of knowledge, challenges, and future directions.

Adrenal incidentalomas are frequently detected on abdominal imaging and require evaluation for malignancy and hormonal activity. Although most are ben...

Multidimensional analysis of tumour immune microenvironment in HCC: prognostic significance and implications for immunotherapy.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) and anti-angiogenic agents represents the standard first-line therapy for patients ...

Development of a predictive model for postoperative body mass index and diabetes outcomes after metabolic bariatric surgery: retrospective cohort study.

BACKGROUND: Predicting postoperative body mass index (BMI) trajectories and long-term type 2 diabetes (T2D) remission after bariatric surgery remains ...

A multimodal deepsurv approach: integrating radiomics and clinical factors for brain metastasis survival prediction.

PURPOSE: Predicting survival outcomes for brain metastasis (BM) patients is crucial for tailoring treatment strategies and improving patient managemen...

New approach methodologies (NAMs) for preclinical and translational evaluation of mRNA-lipid nanoparticle (LNP) therapeutics.

Messenger RNA-lipid nanoparticle (mRNA-LNP) therapeutics have emerged as a versatile drug modality, enabling in vivo protein expression for vaccines, ...

Face/off: phase-specific modeling of lineage plasticity using near-patient models in genitourinary cancers.

Lineage plasticity has emerged as a fundamental mechanism of adaptive therapy resistance in prostate and bladder cancers, enabling malignant cells to ...

Benchmarking Zero-Shot Generative Pre-Trained Transformer-Based Multimodal Large Language Models for Pressure Injury Staging.

OBJECTIVE: To benchmark zero-shot generative pre-trained transformer (GPT)-based multimodal large language models (MLLMs) for pressure injury (PI) sta...

Extending responsible artificial intelligence to palliative care: the irreversibility problem with algorithmic accountability.