AIMC Topic: Biomarkers, Tumor

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Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients.

Cancer medicine
BACKGROUND: Cancer biomarkers play a pivotal role in the diagnosis, prognosis, and treatment response prediction of the disease. In this study, we analyzed the expression levels of RhoB and DNp73 proteins in rectal cancer, as captured in immunohistoc...

Translation of tissue-based artificial intelligence into clinical practice: from discovery to adoption.

Oncogene
Digital pathology (DP), or the digitization of pathology images, has transformed oncology research and cancer diagnostics. The application of artificial intelligence (AI) and other forms of machine learning (ML) to these images allows for better inte...

Enlightening the path to NSCLC biomarkers: Utilizing the power of XAI-guided deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The early diagnosis of Non-small cell lung cancer (NSCLC) is of prime importance to improve the patient's survivability and quality of life. Being a heterogeneous disease at the molecular and cellular level, the biomarkers r...

The impact of misclassification errors on the performance of biomarkers based on next-generation sequencing, a simulation study.

Journal of biopharmaceutical statistics
The development of next-generation sequencing (NGS) opens opportunities for new applications such as liquid biopsy, in which tumor mutation genotypes can be determined by sequencing circulating tumor DNA after blood draws. However, with highly dilute...

Hybrid chain reaction and selective recognition-based homogeneous dual-fluorescence analysis of circulating tumor cells in clinical ovarian cancer samples.

Analytica chimica acta
BACKGROUND: Oncological analysis is important in tumor diagnosis. We constructed a dual-fluorescence and binary visual analysis system for circulating tumor cells (CTCs) using the folate receptor as a biomarker, combined with hybridization chain reac...

Construction of Immune Infiltration-Related LncRNA Signatures Based on Machine Learning for the Prognosis in Colon Cancer.

Biochemical genetics
Colon cancer is one of the malignant tumors with high morbidity, lethality, and prevalence across global human health. Molecular biomarkers play key roles in its prognosis. In particular, immune-related lncRNAs (IRL) have attracted enormous interest ...

Tumor Mutation Burden-Related Histopathologic Features for Predicting Overall Survival in Gliomas Using Graph Deep Learning.

The American journal of pathology
Tumor mutation burden (TMB) is a potential biomarker for evaluating the prognosis and response to immune checkpoint inhibitors, but its costly and time-consuming method of measurement limits its widespread application. This study aimed to identify th...

Deep learning transforms colorectal cancer biomarker prediction from histopathology images.

Cancer cell
Artificial intelligence (AI) is rapidly gaining interest in medicine, including pathological assessments for personalized medicine. In this issue of Cancer Cell, Wagner et al. demonstrate superior accuracy of transformer-based deep learning in predic...

Global serum profiling: an opportunity for earlier cancer detection.

Journal of experimental & clinical cancer research : CR
The advances in cancer research achieved in the last 50 years have been remarkable and have provided a deeper knowledge of this disease in many of its conceptual and biochemical aspects. From viewing a tumor as a 'simple' aggregate of mutant cells an...