AIMC Topic: Immunotherapy

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Pretrained transformers applied to clinical studies improve predictions of treatment efficacy and associated biomarkers.

Nature communications
Cancer treatment has made significant advancements in recent decades, however many patients still experience treatment failure or resistance. Attempts to identify determinants of response have been hampered by a lack of tools that simultaneously acco...

Radiomics and Deep Learning Prediction of Immunotherapy-Induced Pneumonitis From Computed Tomography.

JCO clinical cancer informatics
PURPOSE: Primary barriers to application of immune checkpoint inhibitor (ICI) therapy for cancer include severe side effects (such as potentially life threatening pneumonitis [PN]), which can cause the discontinuation of treatment. Predicting which p...

CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy.

Academic radiology
RATIONALE AND OBJECTIVES: Immunotherapy combined with chemotherapy has improved outcomes for some esophageal squamous cell carcinoma (ESCC) patients, but accurate pre-treatment risk stratification remains a critical gap. This study constructed a deep...

Research trends of neoadjuvant therapy for breast cancer: A bibliometric analysis.

Human vaccines & immunotherapeutics
The approach of neoadjuvant therapy for breast cancer, which involves administering systemic treatment prior to primary surgery, has undergone substantial advancements in recent decades. This strategy is intended to reduce tumor size, thereby enablin...

Improving Outcomes in Hepatocellular Carcinoma through Integration of Machine Learning: Development of a Tumor-Associated Macrophage Signature.

Digestive diseases (Basel, Switzerland)
INTRODUCTION: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally. Macrophages, as essential components of the immune system, play crucial roles in immune regulation, inflammation modulation, and antitumor activity. How...

The clinical application of artificial intelligence in cancer precision treatment.

Journal of translational medicine
BACKGROUND: Artificial intelligence has made significant contributions to oncology through the availability of high-dimensional datasets and advances in computing and deep learning. Cancer precision medicine aims to optimize therapeutic outcomes and ...

Intestinal Microbiome Modulation of Therapeutic Efficacy of Cancer Immunotherapy.

Gastroenterology clinics of North America
Bacteria are associated with certain cancers and may induce genetic instability and cancer progression. The gut microbiome modulates the response to cancer therapy. Training machine learning models with response associated taxa or bacterial genes pre...

Embracing the Future of Clinical Trials in Radiation Therapy: An NRG Oncology CIRO Technology Retreat Whitepaper on Pioneering Technologies and AI-Driven Solutions.

International journal of radiation oncology, biology, physics
This white paper examines the potential of pioneering technologies and artificial intelligence-driven solutions in advancing clinical trials involving radiation therapy. As the field of radiation therapy evolves, the integration of cutting-edge appro...

Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. Manual segmentation of the tumor components is time-consuming and poses significa...