AIMC Topic: Early Detection of Cancer

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A deep learning model to enhance lung cancer detection using 'Dual-Branch' model classification approach.

PloS one
Cancer remains a life-threatening global challenge, with lung cancer ranking among the most devastating forms, impacting millions annually. Early detection and accurate classification are essential for improving patient survival rates, and computed t...

Development of liquid biopsy for screening colorectal cancer through the combination of an antibody microarray-based metal-enhanced sandwich immunofluorescent assay of cytokines with machine learning.

The Analyst
The simultaneous determination of the expression levels of multiple inflammation-associated cytokines in blood holds great promise for the early screening of cancer including colorectal cancer (CRC). Herein, an antibody microarray-based sandwich meta...

A machine-learning informed circulating microbial DNA signature for early diagnosis of esophageal adenocarcinoma.

Gut microbes
Esophageal adenocarcinoma (EAC) has seen a dramatic rise in incidence in developed countries over the past three decades. Early detection of its precursors-gastroesophageal reflux disease (GERD), Barrett's esophagus (BE), and high-grade dysplasia (HG...

Improving Colorectal Cancer Detection with AI-Assisted Colonoscopy: A Systematic Review and Meta-Analysis of 38 RCTs with GRADE Assessment.

Journal of gastrointestinal cancer
BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. Early detection of precancerous lesions such as adenomas and polyps is vital for prevention, yet standard colonoscopy may miss up to 26% of adenomas. A...

3D Total Body Photography as a Promising Innovation for Early Skin Cancer Detection: Scoping Review.

JMIR dermatology
BACKGROUND: Skin cancer (SC) is a global health concern because of its high and still increasing incidence and associated health care cost. Belgium is no exception as 1 in 5 people are diagnosed with SC before the age of 75 years. The VECTRA WB360, a...

[The Development of Algorithm of Intellectual System of Supporting Decision-Making in Mammographic Diagnostics of Breast Cancer Based on Convolutional Neuronic Network].

Problemy sotsial'noi gigieny, zdravookhraneniia i istorii meditsiny
The article considers issues of training models of convolutional neuronic network (CNN) for automated identification of point functions of visualization to discern mammography pictures belonging to negative, false benign and malignant cases, targetin...

Proteomics-Driven Cancer Biomarkers for Early Detection and Targeted Therapy: Insights from the Middle East.

Journal of proteome research
Proteomics has become a transformative tool in oncology, offering unique opportunities for early detection, diagnosis, and cancer stratification. By enabling large-scale analysis of protein expression, interactions, and post-translational modificatio...

The alternative splicing landscape of hepatocellular carcinoma and its potential for HCC detection.

Hepatology communications
BACKGROUND: Pre-mRNA alternative splicing contributes to oncogenic gene expression in hepatocellular carcinoma (HCC), and some oncogenic isoforms escape the tumor into circulation. This study aimed to characterize the alternative splicing landscape o...

The best from both disciplines: integrating human and microbial signatures from whole genome sequencing to advance cancer diagnostics.

mSystems
Liquid biopsies are transforming oncology, enabling earlier diagnosis, dynamic treatment guidance, and personalized precision medicine, yet current approaches focusing mainly on circulating host cell-free DNA (cfDNA) neglect crucial information withi...

Mammo-AGE: deep learning estimation of breast age from mammograms.

Nature communications
Biological age is an important indicator of organ functions and health. Although mammograms are widely used in breast cancer screening, the potential of mammogram-based biological age predictors remains underexplored. Here, we propose a deep learning...