Colon Cancer

Ultrasound-Responsive Serotonylation and Hallmark Pathway Gene Signatures Reveal Tumor Microenvironment Vulnerabilities and Prognostic Subtypes in Colorectal Cancer.

BACKGROUND: Focused ultrasound, low-intensity focused ultrasound, and microbubble-enhanced sonoporation are examples of ultrasound-based cancer therapies that have shown promise as biophysical modalities for enhancing drug penetration, immunogenic cell death, and targeted delivery of radiopharmaceuticals in solid tumors. The molecular factors controlling ultrasonic therapy receptivity, however, ar...

[Utilizing machine learning and SHAP analysis to develop a prognostic survival prediction model for gastric cancer patients following radical gastrectomy].

Objective: To construct a prediction model and website for the overall survival (OS) of gastric cancer patients after radical gastrectomy based on SHapley Additive exPlanations (SHAP) and machine learning models. Methods: This retrospective cohort study included 234 patients who underwent radical gastrectomy at Henan Cancer Hospital from October 2018 to December 2022, selected according to the fol...

EASDnet: Empowering human-centered evidence-based medicine through an evidence and attention-based spatial disparity network for discriminative colorectal cancer histopathological screening and attribution.

PURPOSE: Accurate preoperative staging of colorectal cancer is critical to guide treatment decisions, including eligibility for R0 resection, to reduc...

Familial colorectal cancer: risk factors, screening strategies and personalized medicine.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with approximately 25-30 % of cases exhibiting a familial compo...

Breaking resistance in BRAF-mutant Melanoma: Novel strategies and biomarkers for optimizing targeted therapies.

In metastatic melanoma with a BRAFV600 mutation, inhibitors of BRAF and MEK have improved survival. Resistance may be acquired through late genetic al...

Microbiota-host interaction in colorectal cancer: emerging computational technology, multi-omics integration, and mechanisms.

Colorectal cancer (CRC) remains a major global health burden with the gut microbiome emerging as a critical contributor to tumor initiation and progre...

Environmental toxicant exposure and diabetes risk: An exposome-wide association study integrating mixture effects and molecular mechanisms.

Environmental toxicant exposure has emerged as a potential contributor to diabetes, yet systematic investigations integrating multiple chemicals and b...

Integrative multi-omics refines the molecular subtypes of thyroid cancers and enhances cancer-progression prediction: a retrospective cohort study.

BACKGROUND: Current molecular classification model for thyroid cancer (TC), which relies on BRAF-RAS score genes has limited efficacy in differentiati...

Efficient self-supervised Barlow Twins from limited tissue slide cohorts for colonic pathology diagnostics.

Colorectal cancer (CRC) is one of the few cancers that have an established dysplasia-carcinoma sequence that benefits from screening. Everyone over 50...

Artificial intelligence for the prediction of synchronous and metachronous liver metastasis in colorectal cancer patients: a systematic review and meta-analysis.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer mortality in the world. Liver is the most c...

Research on Lung Cancer Classification Based on Multidimensional Hematological Indicators and Machine Learning Models.

Accurate subtyping of lung cancer is crucial for developing personalized treatment plans and improving patient outcomes. This study established machin...

Noninvasive diagnosis of colorectal adenoma: The emerging potential of blood-based biomarkers.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer-related death globally. Most CRCs arise fro...

Artificial intelligence-supported polyp detection (CADe) at colonoscopy reduces the detection of high grade dysplasia and invasive cancer.

Deep learning-based H&E-derived risk scores in colorectal cancer: associations with tumour morphology, biology, and predicted drug response.

Over recent years, several deep learning (DL) models have been presented to predict colorectal cancer (CRC) patient survival directly from haematoxyli...

Identifying a better-prognosis pancreatic cancer from its benign inflammatory mimic: a machine learning approach with contrast-enhanced ultrasound for early intervention.

PURPOSE: Hypervascular pancreatic ductal adenocarcinoma (PDAC) and mass-forming pancreatitis (MFP) represent a classic diagnostic mimicry on contrast-...

Topologically distinct 2D and 3D intratumoral heterogeneity scores for preoperatively predicting invasiveness in stage I lung adenocarcinoma: A multicenter study.

This multicenter study aims to enhance the preoperative prediction of pathological invasiveness in clinical stage I lung adenocarcinoma (LUAD) by deve...

Driver gene mutations and clinical features predict bone metastasis risk in NSCLC: a logistic regression model.

Bone metastasis affects approximately 40% of patients with non-small cell lung cancer (NSCLC), significantly impacting patient survival and prognosis....

Non-invasive prediction of Ki-67 expression in gastric cancer using AI-based dual-energy CT: a multicenter study.

OBJECTIVE: To develop and validate a machine learning model based on quantitative parameters of dual-energy CT (DECT) virtual monoenergetic images (VM...

Exploring an Intermediate Colorectal Cancer Screening Test Based on Stool Proteomics and Machine Learning for Optimizing the Selection of Patients for Colonoscopy Identified from FIT.

The fecal immunochemical test (FIT) for detecting fecal occult blood, used alone or in combination with other stool biomarkers, has been demonstrated ...

SCMO: a deep learning model integrating the single-cell resolution TME ecosystem and multi-omics for survival prediction in CRC patients.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of global cancer mortality, highlighting the need for precise survival prediction to guide...