Oncology/Hematology

Toward a multi-level, needs-based approach to cancer navigation: Considerations for service design.

Evidence suggests that patient navigation can help address ongoing barriers to accessing timely, appropriate, and quality cancer care. It also supports people affected by cancer to navigate through complex health care systems. Cancer patient navigation interventions include education, logistical, social, and emotional support, facilitating referrals, care coordination, patient advocacy, and enabli...

Integrating Mechanistic Modeling and Machine Learning to Study CD4+/CD8+ CAR-T Cell Dynamics with Tumor Antigen Regulation.

Chimeric antigen receptor (CAR) T cell therapy has shown remarkable success in hematological malignancies, yet patient responses remain highly variable and the roles of CD4+ and CD8+ subsets are not fully understood. We present an extended mathematical framework of CAR-T cell dynamics that explicitly models CD4+ helper and CD8+ cytotoxic lineages and their interactions with tumor antigen burden. B...

An interpretable machine learning model combining MRI-DKI habitat radiomic features and clinical biomarkers for noninvasive prediction of lymphatic metastasis in rectal cancer: a prospective study.

OBJECTIVE: Tumor heterogeneity exerts a significant influence on lymphovascular invasion (LVI) and lymph node metastasis (LNM) in rectal cancer (RC), ...

Dissecting glioblastoma risk signatures in the tumor immune microenvironment based on multi-dimensional transcriptomics.

Glioblastoma (GBM) is characterized by pronounced tumor heterogeneity and a complex immune microenvironment, contributing to poor patient survival out...

Development and Evaluation of a Human-in-the-Loop Data Curation Training Program to Support a Digital Clinical Trial Platform: Descriptive Feasibility Study.

BACKGROUND: LookUpTrials is a clinician-facing digital platform designed to support point-of-care navigation of institution-specific oncology clinical...

[Comprehensive diagnosis and treatment of distal biliary strictures: multidisciplinary collaboration and precision surgical strategies].

Distal biliary strictures (DBS) are a common and complex clinical problem in pancreaticobiliary diseases,with etiologies involving multiple factors su...

Artificial intelligence for detection, grading, and prognostication in prostate cancer pathology: A scoping review.

Artificial intelligence (AI) has been transforming many aspects of medical care. In prostate cancer, ongoing progress in AI has improved research and ...

[Emphasizing whole-course management of colorectal cancer: from diagnosis and treatment to patient health].

With continuous advancements in therapeutic technologies for colorectal cancer, patient survival has been significantly prolonged, increasingly charac...

[Application of multi-parametric vital sign monitoring systems in the integrated management of the perioperative stage of gastric cancer].

The perioperative management of gastric cancer is a crucial factor influencing patient prognosis. The traditional model has limitations such as fragme...

A convolutional neural network for fully automated total metabolic tumor volume delineation in patients with aggressive Non-Hodgkin lymphoma.

PURPOSE: The [18F]FDG-PET-derived total metabolic tumor volume (TMTV) has a high prognostic value in patients with Hodgkin and Non-Hodgkin lymphoma. H...

Enhanced mechanical and shielding properties of heavy concrete: A machine learning approach to mix proportion optimization.

Shielding concrete is a multifunctional material that combines structural support with radiation shielding, offering significant practical value. Howe...

Development of hematopoietic stem cell-targeted lipid nanoparticles through lipid composition optimization.

Hematopoietic stem cell (HSC)-targeted gene editing holds significant potential for treating hereditary hematopoietic disorders, yet the efficient and...

DeepSTFSynergy: A multi-scale structural information fusion method for personalized drug combination prediction.

Efficiently predicting drug synergy is crucial for developing personalized cancer combination therapy regimens. However, existing methods primarily fo...

Integrating liquid biopsies and artificial intelligence for early cancer detection: A systematic review and meta-analysis.

INTRODUCTION: The latest generation of liquid biopsies incorporates multi-omic features, including genomics, methylomics, and fragmentomics. Machine l...

Assessment of a Deep Learning Model Trained on Permanent Pathology for the Classification of Squamous Cell Carcinoma in Mohs Frozen Sections: Lessons Learned.

Improving severity grading of chemotherapy-induced myelosuppression in AML via data-driven and model-based deep learning.

Chemotherapy-induced myelosuppression in acute myeloid leukemia (AML) frequently leads to life-threatening complications, yet current assessment stand...

AI-based chest X-ray prioritization in the lung cancer diagnostic pathway: the LungIMPACT randomized controlled trial.

Prioritizing artificial intelligence (AI)-detected imaging findings may reduce the time to diagnosis of lung cancer. This prospective, multicentre, ra...

Machine learning vs. radiomics for discriminating atypical cartilaginous tumors from benign enchondromas on MRI.

BACKGROUND: Enchondromas (EC) present cartilaginous tumors that are difficult to differentiate from their intermediate counterpart, atypical cartilagi...

Development and validation of an interpretable machine learning model integrating inflammatory blood biomarkers for predicting postoperative breast cancer-related lymphedema: A prospective cohort study.

BACKGROUND: Breast cancer-related lymphedema is a frequent and debilitating complication. Early identification of high-risk individuals is critical, y...

Overall risk of cancer incidence attributable to adult body CT examinations: impact of a seven-year continuous quality improvement program.

OBJECTIVES: To estimate the impact of a continuous dose reduction and quality improvement program on radiation-induced cancer risk in adult computed t...