Latest AI and machine learning research in chemotherapy for healthcare professionals.
Pancreatic cancer is highly aggressive with poor outcomes; current artificial intelligence (AI) prognostic models often lack interpretability and underutilize large-scale data. This study develops an explainable AI prognostic model for pancreatic cancer survival using Taiwan's national registry data, aiming to identify key prognostic factors, their interactions, non-linear relationships, and patie...
The advancement of mRNA technology has rejuvenated the cancer treatment immunotherapy field by providing a flexible and scalable platform to generate tumor-associated or patient-specific neoantigens, which induces strong cytotoxic and helper T-cell outcomes and also immunologically stimulates innate immunity in the body at the same time. In contrast to conventional vaccines, mRNA preparations are ...
OBJECTIVE: To define oncologic outcomes in Veterans in the modern era using a multi-institutional cohort designed to support development and validatio...
IMPORTANCE: Cancer antigen 19-9 (CA19-9) is used to assess treatment response among patients with pancreatic ductal adenocarcinoma (PDAC); however, ne...
Accurate assessment of Human Epidermal Growth Factor Receptor 2 (HER2) immunohistochemistry (IHC) expression, particularly the precise identification ...
The immunological synapse (IS) formed between cytotoxic CD8+ T lymphocytes (CTLs) and tumor cells represents the critical interface where many immunot...
BACKGROUND: Immune checkpoint molecules are pivotal regulators of immune activation and tolerance, playing critical roles in cancer, autoimmunity, inf...
Multi-element alloy catalysts exhibit tunable electronic structures and remarkable thermal stability, making them promising materials for automotive e...
Immunosenescence is a fundamental hallmark of aging, characterized by differential susceptibility across immune cell lineages. T lymphocytes are parti...
Homologous recombination deficiency (HRD) plays a central role in the pathogenesis and therapeutic vulnerability of epithelial ovarian cancer (EOC), p...
INTRODUCTION: Peripherally inserted central catheters (PICCs) are increasingly used in France for prolonged intravenous therapies such as chemotherapy...
Cancer is one of the leading causes of death worldwide, and early tumor detection can significantly reduce mortality rates. Liquid biopsy is a minimal...
PURPOSE: We present MuTriM, a multimodal deep learning model integrating DCE-MRI and whole-slide pathology to predict survival and radiation benefit i...
Accurate nitrite detection in beverages and pickled foods is crucial for food safety but remains challenging due to matrix complexity, particularly in...
OBJECTIVE: To develop and validate a CT-based radiomics model to predict immunotherapy response in unresectable gastric cancer and explore its underly...
BACKGROUND: Genomic assays such as Oncotype DX have transformed adjuvant treatment selection for hormone receptor-positive, HER2-negative, early breas...
This study presents an integrated methodology for pre-operative cryosurgical planning of irregularly shaped brain tumors using two-dimensional MRI dat...
Breast cancer heterogeneity limits the precision of current prognostic and therapeutic strategies, underscoring the need for molecular frameworks that...
BACKGROUND AND PURPOSE: Â Soft tissue sarcomas are a heterogeneous group of malignant tumors with a high risk of metastasis, primarily to the lungs, ma...
OBJECTIVE: To develop an interpretable multimodal model that integrates pre-treatment Magnetic resonance imaging (MRI)-based deep learning radiomics (...