Oncology/Hematology

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 structures. Achieving optimal tumor resection while minimizing neurological deficits requires advanced decision-making strategies. This case report explores the integration of an explainable artificial intelligence (AI) system into the neurosurgical ...

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 intelligence (AI) models to integrated, agentic systems across oncology. Platforms such as Synapse enable large-scale data coordination, supporting interoperable and reproducible research. Building on this foundation, conversational and multi-agent AI tools (e....

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 ...

Comprehensive identification of three key genes and three key DNA methylation CpG sites associated with prognosis and prediction in colon adenocarcinoma.

Colon adenocarcinoma (COAD) is a common cancer with high incidence and mortality rates worldwide. DNA methylation has a significant impact on the occu...

Integrating Participatory Social Innovation Into Requirements Engineering for AI Health Care Solutions: Case Study.

BACKGROUND: The successful design and implementation of artificial intelligence (AI)-driven solutions in health care requires early and continuous mul...

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...

Comment on "Artificial intelligence-driven body composition analysis enhances chemotherapy toxicity prediction in colorectal cancer".

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.

Multi-scale and context-aware enhanced YOLOv8 for breast tumor detection in ultrasound images.

Early and accurate detection of breast tumors via ultrasound imaging is paramount for effective clinical intervention. While single-stage object detec...

A hybrid quantum-classical framework for MRI-based deep brain tumor segmentation and classification.

The characterization of brain tumors from magnetic resonance imaging (MRI) is crucial for diagnosis, treatment planning, and prognosis. But the analys...

Pan-cancer analysis of tissue-plasma genomic concordance reveals enhanced concordance with liver metastasis and plasma clonality as predictor of poorer overall survival.

Circulating tumor DNA (ctDNA) enables noninvasive tumor genotyping, yet its concordance with tissue remains unclear. Using a 437-gene panel in 1111 pa...

Anatomically constrained deep learning for clinical-grade volumetric pancreatic cancer segmentation: development, validation, and architectural benchmarking.

Automated segmentation of PDAC is a prerequisite to realize the promise of precision oncology, yet existing approaches remain insufficiently validated...