AIMC Topic: Biomarkers, Tumor

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Comparative machine learning analysis for predicting organ tropism in breast cancer and identifying key gene signatures.

Computers in biology and medicine
BACKGROUND: Breast cancer metastasis (BCM) metastasizes preferentially to certain organs. Important genetic markers can be used for early detection and treatment. Machine learning (ML) can efficiently handle gene expression data to enhance metastasis...

Biomarker discovery for early breast cancer diagnosis using machine learning on transcriptomic data for biosensor development.

Computers in biology and medicine
Breast cancer is the second leading cause of female mortality globally. Effective diagnostic tools, such as biosensors that utilize reliable biomarkers, are essential for early detection, particularly in low-income countries. This study introduces a ...

Machine Learning-Assisted Multimodal Early Screening of Lung Cancer Based on a Multiplexed Laser-Induced Graphene Immunosensor.

ACS nano
Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis. Early detection is critical for improving patient outcomes, yet current screening methods, such as low-dose computed tomography (CT), of...

Urine-based Raman markers for prostate cancer diagnosis: A machine learning approach using fingerprint and lipid spectral region.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study investigates the potential of Raman spectroscopy in distinguishing between healthy individuals and prostate cancer patients using urine samples. The Boruta algorithm was applied to Raman spectral data in two distinct wavenumber regions: 80...

A noninvasive and highly efficient epigenetic predictive model for efficacy of the GOLP regimen in patients with intrahepatic cholangiocarcinoma.

Cancer letters
The GOLP regimen (Gemcitabine, Oxaliplatin, Lenvatinib and anti-PD1 antibody) has been a promising first-line treatment for advanced intrahepatic cholangiocarcinoma (iCCA). A noninvasive tool to predict the response to GOLP regimen is needed for clin...

Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics.

Scientific reports
Glioma is a highly heterogeneous and aggressive brain tumour that demands an integrated understanding of its molecular and immunological landscape. We collected multi-omics data from 575 TCGA diffuse-glioma patients (156 IDH-wild-type WHO-grade 4 gli...

Exploration and validation of the prognostic value of mitophagy and mitochondrial dynamics-related genes in cervical cancer.

Scientific reports
The mechanisms underlying mitophagy and mitochondrial dynamics (MD) in cervical cancer (CC), a disease with a high mortality rate, remain poorly understood. This study aimed to assess the prognostic significance of these processes in CC. Mendelian ra...

oDigital pathology biomarkers for guiding radiotherapy-based treatment concepts in prostate cancer - a systematic review and expert consensus.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Current risk-stratification systems for prostate cancer (PCa) do not sufficiently reflect the disease heterogeneity, and digital pathology (DP) combined with artificial intelligence (AI) tools (DP-AI) may offer a solution to this challenge. The aim o...

The correlation of liquid biopsy genomic data to radiomics in colon, pancreatic, lung and prostatic cancer patients.

European journal of cancer (Oxford, England : 1990)
INTRODUCTION: With the advances in artificial intelligence (AI) and precision medicine, radiomics has emerged as a promising tool in the field of oncology. Radiogenomics integrates radiomics with genomic data, potentially offering a non-invasive meth...

OMT and tensor SVD-based deep learning model for segmentation and predicting genetic markers of glioma: A multicenter study.

Proceedings of the National Academy of Sciences of the United States of America
Glioma is the most common primary malignant brain tumor and preoperative genetic profiling is essential for the management of glioma patients. Our study focused on tumor regions segmentation and predicting the World Health Organization (WHO) grade, i...