AIMC Topic: Neoplasms

Clear Filters Showing 1711 to 1720 of 2356 articles

[Opportunities and challenges in the pathological diagnosis of pediatric tumors in the molecular and artificial intelligence era].

Zhonghua bing li xue za zhi = Chinese journal of pathology
Pediatric tumors differ significantly from adult cancers, possessing unique developmental origins, histological features, and molecular genetic changes. With the rapid advancement of multi-omics technologies, such as genomics, transcriptomics, proteo...

From Innovation to Impact: Advancing Cancer Research Together.

Cancer discovery
Cancer research has entered a transformative era, marked by rapid advances in immunotherapy, early detection, precision oncology, and artificial intelligence that are reshaping prevention, treatment, and survivorship. To sustain momentum, the global ...

Prediction of mortality in cancer patients with COVID-19 using machine learning methods.

Medicine
This study aimed to predict mortality in cancer patients diagnosed with COVID-19 using machine learning (ML) algorithms and identify the clinical and laboratory parameters associated with mortality. Demographic, clinical, and laboratory data of cance...

Genetic Control of tRNA-Derived Fragments Contributes to Cancer Risk.

Cancer research
UNLABELLED: tRNA-derived fragments (tRF) are a class of small noncoding RNAs that have exhibited several functions in cancer. Recent studies have shown that mutations in tRNA genes can lead to global changes in tRF expression levels and may affect tR...

Heterogeneous Driving Effects Guide Personalized Tumor Treatments Targeting N6-Methyladenosine.

Cancer research
UNLABELLED: Alterations to N6-methyladenosine (m6A) modifications can promote malignant progression by modulating gene expression through regulation of transcript metabolism. Quantifying the causal impact of m6A dysregulation at the population level ...

From Harmony to Discord: Multicellular Coordination in Tissues and Its Rewiring in Cancer.

Cancer research
Tissue function emerges from coordinated interactions among diverse cell types, but how these interactions are structured and rewired in disease remains unclear. In a recent study, Shi and colleagues introduce CoVarNet, a computational framework that...

Artificial intelligence in predicting efficacy and toxicity of Immunotherapy: Applications, challenges, and future directions.

Cancer letters
Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, becoming a standard approach for various tumor types. Consequently, accurately predicting their efficacy has become crucial in clinical practice. Artificial intelligence (AI) h...

Translating Artificial Intelligence Breakthroughs into Cancer Diagnostic Breakthroughs.

Cancer discovery
The revolution of artificial intelligence has yet to find its way into clinical practice in oncology. We highlight eight specific challenges, focused on diagnostics, that will enable this translation once they are adequately addressed.

Framework to Select Multi-Cancer Detection Assays in the National Cancer Institute's Vanguard Study.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
BACKGROUND: The Cancer Screening Research Network is a new clinical trials network funded by the NCI. The first Cancer Screening Research Network study, the Vanguard Study (VS), will assess the feasibility of using multi-cancer detection (MCD) tests ...

Neoantigen-driven personalized tumor therapy: An update from discovery to clinical application.

Chinese medical journal
Neoantigens exhibit high immunogenic potential and confer a uniqueness to tumor cells, making them ideal targets for personalized cancer immunotherapy. Neoantigens originate from tumor-specific genetic alterations, abnormal viral infections, or other...