Oncology/Hematology

Advances in immune checkpoint inhibitor therapy for microsatellite instability-high (MSI-H) and mismatch repair-deficient (dMMR) colorectal cancer: Insights from the tumor immune microenvironment.

This review systematically analyzes the relationship between the immune microenvironment characteristics of microsatellite instability-high (MSI-H) or deficient mismatch repair (dMMR) colorectal cancer (CRC) and the efficacy of immune checkpoint inhibitors (ICIs). The article emphasizes that this tumor subtype has a high mutation burden, abundant neoantigens, and significant immune cell infiltrati...

Topology-Aware Deep Learning on Higher-Order Structures for Drug Response Prediction.

Accurate prediction of anticancer drug response remains a central challenge in precision oncology. Existing approaches often rely on pairwise modeling, overlooking higher-order dependencies among drugs and cell lines. We present TopDr, a topology-aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0-, 1-, and 2-simp...

AI as a Safety-Net Reader for Mammograms Classified as Normal or Benign in the French Screening Program.

In the French national breast cancer screening program, second reading is performed only for mammograms interpreted as negative (BI-RADS 1-2) at first...

Elucidating the molecular mechanisms linking bisphenol A to breast cancer: an integrated study of bioinformatics, machine learning, and molecular docking.

Bisphenol A (BPA) is a prevalent environmental endocrine disruptor linked to breast cancer. However, the precise molecular mechanisms and core therape...

Investigation of the clinical value of artificial intelligence-derived prognostic signature in cervical cancer based on machine learning algorithms.

Women around the world are troubled by life-threatening cervical cancer. It is urgent to identify a biomarker to improve the prognosis of cervical can...

PhosSight: A Unified Deep Learning Framework Boosting and Accelerating Phosphoproteome Identification to Enable Biological Discoveries.

Protein phosphorylation is a key regulator of signaling, with mass spectrometry (MS) based phosphoproteomics serving as the premier technology for its...

Multimodal Prediction of Renal Tumor Malignancy From Radiology Reports and Structured Electronic Health Records: Retrospective Cohort Study.

BACKGROUND: Accurate preoperative prediction of renal tumor malignancy is critical for guiding decisions and reducing overtreatment, as a substantial ...

Prediction of cancer-associated thrombosis by machine learning: results from the Vienna Cancer and Thrombosis Study.

BACKGROUND: Improved risk prediction of cancer-associated venous thromboembolism (VTE) remains an unmet clinical need. We aimed to apply machine learn...

Multimodal Deep Learning for Benign vs Malignant Eyelid Lesion Classification Using Optical Coherence Tomography and Clinical Images.

PURPOSE: To evaluate the performance of deep learning models using optical coherence tomography (OCT) volumes, clinical photographs, and their multimo...

What do UK hospice websites communicate about the meaning of palliative care?

OBJECTIVES: Hospice websites are an important source of information for the public. This study examined whether information communicated about palliat...

Interpretable machine learning model using peripheral blood for non-invasive detection of moderate-to-severe myelofibrosis in JAK2 V617F-positive MPNs: A multicentre pilot proof-of-concept study.

Progression to moderate-to-severe myelofibrosis (MF) in JAK2 V617F-positive myeloproliferative neoplasms (MPNs) is often clinically silent, and bone m...

[Stratified application of CA19-9 in the surveillance of postoperative recurrence of pancreatic cancer].

Pancreatic cancer is characterized by high postoperative metastasis and recurrence rates, making the identification of early recurrence markers with h...

[MRI-based deep learning model for preoperative prediction of urothelial carcinoma with variant histology of bladder: a retrospective, multicenter study].

Objectives: To develop a deep learning model based on magnetic resonance imaging (MRI) for the preoperative prediction of urothelial carcinoma with va...

Interpretable Deep Learning Radiomics Model for Preoperative Prediction of High-Grade Soft Tissue Sarcomas: A Multicenter MRI Study.

This study aims to develop a preoperative fat-suppressed T2-weighted imaging (FS-T2WI)-based deep learning radiomics (DLR) model for predicting high-g...

Psychological distress in cancer survivors: a population-based analysis and machine learning-based risk stratification.

PURPOSE: As the number of cancer survivors increases, psychological distress has become an important issue. Using nationally representative data, we e...

Applying artificial intelligence and machine learning framework for de novo design of pyrazole-based VEGFR-2 inhibitors.

VEGFR-2 is an important target for oncological interventions due to its key role in angiogenesis, a biological process vital for tumour expansion and ...

Evolution of Gastrointestinal Inflammatory Diseases and Neoplasm Burden in Super-Elderly Populations: Integrated GBD 2023, CHARLS, and CLHLS Analyses of China and G20 Countries.

BACKGROUND: Rapid population aging has profoundly altered the epidemiological profile of gastrointestinal diseases in individuals aged ≥75 years. Alth...

Decoding lactylation heterogeneity in glioblastoma: machine learning identifies G6PC3 as a prognostic target.

BACKGROUND: Glioblastoma (GBM) is the most common malignant glioma in adults. It has an extremely poor prognosis, highlighting an urgent need for new ...

Exploring the value of peritumoral brain zone for classification of two malignant brain tumors based on the MRI interpretable models.

OBJECTIVES: This study aims to develop and validate a novel multimodal interpretable artificial intelligence model capable of fusing radiomics feature...

Artificial intelligence in population-based cancer screening: evidence from a national survey of Italian professionals.

BACKGROUND: Artificial Intelligence (AI) is increasingly proposed to enhance population-based cancer screening. While several applications are under e...