Oncology/Hematology

Integrating DNA methylation biomarkers for breast cancer risk prediction using artificial intelligence.

Breast cancer remains a major cause of morbidity and mortality among women worldwide, highlighting the necessity for predictive tools to identify at-risk individuals prior to the manifestation of symptoms. Standard imaging, like mammography, has limited sensitivity in dense breasts and relies on visible morphological changes. In contrast, circulating DNA methylation biomarkers provide a minimally ...

Targeting m6A-SCG2-TAMs axis overcomes 5-FU resistance in colorectal cancer via a multi-omics model.

Chemoresistance to 5-fluorouracil (5-FU) remains a critical barrier in colorectal cancer (CRC) management. This study integrates multi-omics data from 26,192 human samples to elucidate the RNA methylation-mediated crosstalk between tumor-associated macrophages (TAMs) and tumor cells. Machine learning models were able to effectively stratify patients by risk and identified a core signature of six g...

Predicting response to neoadjuvant therapy using artificial intelligence on digitized histopathology slides: a systematic review.

Neoadjuvant therapy (NAT) is an important treatment strategy in surgical oncology, but not all patients benefit equally from it. This systematic revie...

Multi-omics and metabolic flux modeling reveal that macrophage CYP27A1-derived 26-hydroxycholesterol drives immunosuppression and cancer malignancy.

Emerging evidence indicates that aberrant cholesterol metabolism in macrophages plays a role in tumorigenesis, however, how specific metabolites relea...

A machine-learning-derived multi-cell death mode signature predicts melanoma prognosis and reveals an immune-cold tumor microenvironment.

BACKGROUND: Regulated cell death programs influence melanoma progression and antitumor immunity, yet a robust prognostic model integrating multiple ce...

Improving pancreatic adenocarcinoma prognosis models through ligand receptor interactions and histopathological integration.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) has an extremely poor prognosis, and existing prognostic markers fail to fully capture the complex hetero...

SpaHNR: a spatial domain identification method via sparse attention-based hierarchical node representation and multi-view contrastive learning.

BACKGROUND: Leveraging deep learning on spatial transcriptomics data enables the identification of distinct spatial domains within tissues, thereby cl...

A predictive model for pathological complete response in neoadjuvant-treated breast cancer: integrating pretreatment clinicopathologic and contrast-enhanced ultrasound characteristics via interpretable machine learning.

BACKGROUND: The ability to predict pathological complete response (pCR) prior to neoadjuvant therapy (NAT) would inform and facilitate tailored therap...

Single-session agreement of ChatGPT and Gemini treatment recommendations with multidisciplinary tumor board decisions in thoracic oncology.

BACKGROUND: To evaluate the single-session agreement between treatment recommendations generated by ChatGPT and Gemini and real-world decisions made b...

Routine biomarkers map response probability in HER2-positive breast cancer treated with neoadjuvant chemotherapy and dual HER2 blockade.

BACKGROUND: Pathologic complete response (pCR) after neoadjuvant chemotherapy and dual HER2 blockade is associated with improved outcomes in HER2-posi...

Leveraging multimodal cancer immunotherapy to amplify the efficacy of oncolytic viruses.

Oncolytic viruses (OVs) represent a versatile platform for cancer immunotherapy, capable of selectively infecting and lysing tumor cells while trigger...

Radiomics-Based AI for the Diagnosis and Prognosis of Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.

BACKGROUND: Vessels encapsulating tumor clusters (VETCs), a CD34-positive vascular pattern in hepatocellular carcinoma (HCC), are linked to aggressive...

High-sensitivity photoelectric sensing of apatinib for recurrent hepatocellular carcinoma in TACE.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, with transcatheter arterial chemoembolization (TACE) being a widel...

Forging New Pathways in Oncology: Strategic Insights from the 17th Annual Frontiers in Cancer Science Conference.

The 17th Annual Frontiers in Cancer Science (FCS) conference (2025) highlighted the convergence of multiomics, computational biology, and ancestry-spe...

Extracting Medical Information From Unstructured Clinical Text Using Large Language Models to Enhance Health Care Interoperability: Proof-of-Concept Study.

BACKGROUND: Unstructured clinical text remains a major barrier to interoperable data reuse and large-scale secondary analysis in health care. Large la...

ChemoCardioNet: An Explainable Multimodal Transformer for Early Prediction of Chemotherapy-Induced Cardiotoxicity.

Chemotherapy-induced cardiotoxicity (CIC) remains a major cause of morbidity and mortality among cancer survivors, and conventional monitoring often f...

Comment on "MRI and PET-Based Machine Learning Radiomics for Metastasis Prediction in Pancreatic Ductal Adenocarcinoma: A Systematic Review".

Attitudes and Needs of Health Care Providers Toward Artificial Intelligence-Assisted Pediatric Palliative Care: Mixed Methods Study.

BACKGROUND: While artificial intelligence's (AI's) transformative potential in health care is widely acknowledged, its application in highly sensitive...

Clinical Variable-Based Machine Learning for Predicting Early mCRPC Using Exclusively Clinical Variables: Development and Multicenter External Validation.

BACKGROUND AND OBJECTIVE: Metastatic hormone-sensitive prostate cancer (mHSPC) exhibits heterogeneous progression patterns, with early progression to ...

Single-cell and machine learning-based neural regulation signature for prognosis prediction and immunotherapy response in lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma (LUAD) molecular heterogeneity limits traditional prognostic models. Given the emerging role of neural regulation (NR) ...