AIMC Topic: Neoplasm Staging

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A clinical decision support system optimising adjuvant chemotherapy for colorectal cancers by integrating deep learning and pathological staging markers: a development and validation study.

The Lancet. Oncology
BACKGROUND: The DoMore-v1-CRC marker was recently developed using deep learning and conventional haematoxylin and eosin-stained tissue sections, and was observed to outperform established molecular and morphological markers of patient outcome after p...

Clavien-Dindo classification and risk prediction model of complications after robot-assisted radical hysterectomy for cervical cancer.

Journal of robotic surgery
Although significant progress has been made with surgical methods, the incidence of complications after minimally invasive surgery in patients with cervical cancer remains high. Established as a standardized system, Clavien-Dindo classification (CDC)...

Diagnostic Accuracy of Deep Learning and Radiomics in Lung Cancer Staging: A Systematic Review and Meta-Analysis.

Frontiers in public health
BACKGROUND: Artificial intelligence has far surpassed previous related technologies in image recognition and is increasingly used in medical image analysis. We aimed to explore the diagnostic accuracy of the models based on deep learning or radiomics...

Combination of CDX2 H-score quantitative analysis with CD3 AI-guided analysis identifies patients with a good prognosis only in stage III colon cancer.

European journal of cancer (Oxford, England : 1990)
AIM: Stratification of colon cancer (CC) of patients with stage II and III for risk of relapse is still needed especially to drive adjuvant therapy administration. Our study evaluates the prognostic performance of two known biomarkers, CDX2 and CD3, ...

The pathological risk score: A new deep learning-based signature for predicting survival in cervical cancer.

Cancer medicine
PURPOSE: To develop and validate a deep learning-based pathological risk score (RS) with an aim of predicting patients' prognosis to investigate the potential association between the information within the whole slide image (WSI) and cervical cancer ...

DiaDeL: An Accurate Deep Learning-Based Model With Mutational Signatures for Predicting Metastasis Stage and Cancer Types.

IEEE/ACM transactions on computational biology and bioinformatics
Mutational signatures help identify cancer-associated genes that are being involved in tumorigenesis pathways. Hence, these pathways guide precision medicine approaches to find appropriate drugs and treatments. The pattern of mutations varies in diff...

Objective and Subjective Assessment of Bladder Function after Robot-assisted Laparoscopic Radical Hysterectomy for Early-stage Cervical Cancer.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To examine whether objective bladder function after robot-assisted radical hysterectomy (RRH) for early-stage cervical cancer is correlated with subjective patient-reported outcomes and quality of life during the first year after RRH...

Deep learning with whole slide images can improve the prognostic risk stratification with stage III colorectal cancer.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Adjuvant chemotherapy is recommended as standard treatment for colorectal cancer (CRC) with stage III according to TNM stage. However, outcomes are varied even among patients receiving similar treatments. We aimed to develop...

A novel deep learning prognostic system improves survival predictions for stage III non-small cell lung cancer.

Cancer medicine
BACKGROUND: Accurate prognostic prediction plays a crucial role in the clinical setting. However, the TNM staging system fails to provide satisfactory individual survival prediction for stage III non-small cell lung cancer (NSCLC). The performance of...

The future of early cancer detection.

Nature medicine
A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish in...