Oncology/Hematology

A myeloid immunosuppressive phenotype defines primary refractoriness to atezolizumab Plus bevacizumab in hepatocellular caarcinoma.

BACKGROUND: Despite improved outcomes with atezolizumab plus bevacizumab (A+B) in hepatocellular carcinoma (HCC), primary refractoriness (PRef), characterised by early progression or short-lived disease stabilisation following treatment, remains a significant challenge. METHODS: We analysed 1296 patients with HCC treated with frontline A+B (AB-real) and validated findings in 645 trial participants...

Multimodal multitask deep learning for grading management system in non-small cell lung cancer.

Accurate histologic subtyping, tumor node metastasis classification (TNM) staging and prognostic assessment are central to clinical management of non-small cell lung cancer (NSCLC), but remain challenging because of tumor heterogeneity, limited biomarker performance and diagnostic uncertainty. Here we show that a multimodal, multi-task deep learning scoring system (MM-DLS), integrating pretreatmen...

Development and validation of a radiomics-dosiomics model for predicting radiotherapy response in locally advanced, unresectable non-small cell lung cancer: a multi-center study.

Early assessment of treatment response is essential for optimizing cancer management, as it allows timely interventions during the course of therapy, ...

Robust artificial intelligence frameworks for lung cancer subtyping and malignancy detection on thoracic CT.

Accurate characterization of thoracic malignancies on computed tomography (CT) remains challenging because histological subtype differentiation and no...

Multimodal fusion-based prediction of postoperative survival in gallbladder adenocarcinoma: Model development and validation.

Accurate prognostic models are essential for optimizing treatment strategies in gallbladder adenocarcinoma (GBAC). We preliminarily constructed and va...

Plasma proteomic signatures of cellular aging predict human disease.

Aging is asynchronous across cells and organs. Here we tested whether plasma proteomics can be used to analyze cell type-specific aging. From analyses...

Effectiveness of Artificial Intelligence in the Automatic Diagnosis of Lesions Detected in Panoramic Radiographs.

This study was aimed at evaluating the effectiveness of artificial intelligence (AI) in detecting jaw cysts and tumors, analyzing lesion content, and ...

Longitudinal validation of ENLIGHT, an AI predictor of immunotherapy response and resistance, in pan-cancer cohorts.

Artificial intelligence (AI) algorithms such as ENLIGHT and DeepPT represent promising approaches to identify predictive biomarkers for immune checkpo...

Integrating ultrasound-CT-MR for preoperative multi-task prediction in ovarian cancer: achieving diagnostic parity with multidisciplinary team consensus.

Ovarian cancer, with high mortality, demands accurate preoperative assessment to guide individualized treatment. It typically requires ultrasound, CT,...

Deep learning analysis of breast cancer histology predicts ATM pathogenic variant carrier status.

We performed deep learning analysis of histopathological whole-slide (full-face) images (WSI) to predict ATM pathogenic or likely pathogenic variant (...

Non-invasive imaging diagnostic techniques in metabolic dysfunction-associated steatotic liver disease: a roadmap for clinicians.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed nonalcoholic fatty liver disease (NAFLD), is the most prevalent ch...

Alcohol consumers' receptivity to artificial intelligence-generated alcohol-cancer risk messages: An experimental study.

BACKGROUND: Alcohol is a group 1 carcinogen linked to seven cancers, yet awareness of this risk remains low in the United State. Identifying effective...

Proteomics as a Theranostic Compass in BCR::ABL1-Negative Myeloproliferative Neoplasms: Integrating Biomarker Discovery with Therapeutic Stratification.

Classic BCR::ABL1-negative myeloproliferative neoplasms (MPNs)-polycythaemia vera, essential thrombocythaemia, and primary myelofibrosis-are clonal ha...

A comparative study of machine learning models for microbiome-based diagnosis and multi-class staging of colorectal cancer.

Colorectal cancer (CRC) is closely associated with gut microbiota dysbiosis; however, comprehensive benchmarking of machine learning models that integ...

CME-KGDTI: integrating clustered mutations into knowledge graph embedding for drug-target interaction prediction.

BACKGROUND: Computational prediction of drug-target interaction (DTI) is critical for drug discovery and precision medicine. Herein, we constructed a ...

Decoding Spectral Perturbations from a SERS Artificial Nose in Serum for Early Lung Cancer Detection.

Serum biomarkers for early cancer detection often suffer from limited sensitivity and specificity due to the biochemical complexity of blood. Here, we...

Oncotype DX: Clinical Utility, Evidence, and Future Trends in Personalized Breast Cancer Management.

The Oncotype DX assay has revolutionized the management of early-stage, hormone receptor-positive, HER2-negative breast cancer. Developed in 2004, it ...

Circulating DNA reveals nucleosome occupancy patterns that are associated with nucleosome-DNA affinity and are affected in cancer.

BACKGROUND: The study of cell-free circulating DNA (cirDNA) fragments (fragmentomics) from liquid biopsies has received increasing attention to detect...

A Review of the Australian MRI Linac Program: From Pie in the Sky to Research Milestone.

The Australian Magnetic Resonance Imaging (MRI) Linear Accelerator program (MRI linac) was a major research project that aimed to build and test a uni...

Spatial-temporal recurrence patterns of grade 4 glioma using deep learning integrated multiparametric MRI and molecular pathology.

Grade 4 glioma is inherently lethal due to inevitable recurrence. Current radiotherapy guidelines recommend uniform target volume margins, disregardin...