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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...

A retrospective analysis using deep-learning models for prediction of survival outcome and benefit of adjuvant chemotherapy in stage II/III colorectal cancer.

Journal of cancer research and clinical oncology
PURPOSE: Most of Stage II/III colorectal cancer (CRC) patients can be cured by surgery alone, and only certain CRC patients benefit from adjuvant chemotherapy. Risk stratification based on deep-learning from haematoxylin and eosin (H&E) images has be...

Robot-assisted versus laparoscopic minimally invasive surgery for the treatment of stage I endometrial cancer.

Gynecologic oncology
OBJECTIVE: Recent reports in both cervical and endometrial cancer suggest that minimally invasive surgery (MIS) had an unanticipated negative impact on long-term clinical outcomes, including recurrence and death. Given increasing use of robotic surge...