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Precision Health Database


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Cancer

Last data update: Sep 27, 2023. (Total: 61652 Documents since 2012)
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Use of artificial intelligence in the management of T1 colorectal cancer: a new tool in the arsenal or is deep learning out of its depth?
James Weiquan Li et al. Clin Endosc 2023
A Systematic Review and Meta-analysis of Convolutional Neural Network in the Diagnosis of Colorectal Polyps and Cancer.
Kamyab Keshtkar et al. Turk J Gastroenterol 2023
An interpretable deep learning framework for predicting liver metastases in postoperative colorectal cancer patients using natural language processing and clinical data integration.
Jia Li et al. Cancer Med 2023
Multi-center evaluation of machine learning-based radiomic model in predicting disease free survival and adjuvant chemotherapy benefit in stage II colorectal cancer patients.
Hui Zhu et al. Cancer Imaging 2023 23(1) 74
Calibration and Validation of the Colorectal Cancer and Adenoma Incidence and Mortality (CRC-AIM) Microsimulation Model Using Deep Neural Networks.
Vahab Vahdat et al. Med Decis Making 2023 272989X231184175
The use of artificial intelligence to identify subjects with a positive FOBT predicted to be non-compliant with both colonoscopy and harbor cancer.
Tom Konikoff et al. Dig Liver Dis 2023
Deep Learning Empowers Endoscopic Detection and Polyps Classification: A Multiple-Hospital Study.
Ming-Hung Shen et al. Diagnostics (Basel) 2023 13(8)
Artificial Intelligence Applied to Colonoscopy: Is It Time to Take a Step Forward?
Antonio Z Gimeno-García et al. Cancers (Basel) 2023 15(8)
Prescription Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) and Incidence of Depression Among Older Cancer Survivors With Osteoarthritis: A Machine Learning Analysis.
Nazneen Fatima Shaikh et al. Cancer Inform 2023 2211769351231165161
Application of artificial intelligence in diagnosis and treatment of colorectal cancer: A novel Prospect.
Zugang Yin et al. Frontiers in medicine 2023 101128084
Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening.
Marco Spadaccini et al. Diagnostics (Basel, Switzerland) 2023 13(6)
Artificial Intelligence in Pediatric Endoscopy: Current Status and Future Applications.
Jasbir Dhaliwal et al. Gastrointestinal endoscopy clinics of North America 2023 33(2) 291-308
Development and validation of machine learning models for postoperative venous thromboembolism prediction in colorectal cancer inpatients: a retrospective study.
Li Qin et al. Journal of gastrointestinal oncology 2023 14(1) 220-232
Radiomics approach with deep learning for predicting T4 obstructive colorectal cancer using CT image.
Lin Pan et al. Abdominal radiology (New York) 2023
A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks.
Adrian Krenzer et al. Journal of imaging 2023 9(2)
Computer-Assisted Diagnosis of Lymph Node Metastases in Colorectal Cancers Using Transfer Learning With an Ensemble Model.
Amjad Khan et al. Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc 2023 36(5) 100118
A machine learning tool for identifying non-metastatic colorectal cancer in primary care.
Elinor Nemlander et al. European journal of cancer (Oxford, England : 1990) 2023 182100-106
Detection of Colorectal Polyps from Colonoscopy Using Machine Learning: A Survey on Modern Techniques.
Khaled ELKarazle et al. Sensors (Basel, Switzerland) 2023 23(3)
Artificial intelligence empowers the second-observer strategy for colonoscopy: a randomized clinical trial.
Pu Wang et al. Gastroenterology report 2023 11goac081
Systematic review of machine learning-based radiomics approach for predicting microsatellite instability status in colorectal cancer.
Wang Qiang et al. La Radiologia medica 2023
Clinical Evaluation of Computer-Aided Colorectal Neoplasia Detection Using a Novel Endoscopic Artificial Intelligence: A Single-Center Randomized Controlled Trial.
Nakashima Hirotaka et al. Digestion 2023 1-9
Construction and validation of nomograms combined with novel machine learning algorithms to predict early death of patients with metastatic colorectal cancer.
Zhang Yalong et al. Frontiers in public health 2023 101008137
A Privacy-Preserving Distributed Medical Data Integration Security System for Accuracy Assessment of Cancer Screening: Development Study of Novel Data Integration System.
Miyaji Atsuko et al. JMIR medical informatics 2022 10(12) e38922
A Review of Radiomics in Predicting Therapeutic Response in Colorectal Liver Metastases: From Traditional to Artificial Intelligence Techniques.
Alshohoumi Fatma et al. Healthcare (Basel, Switzerland) 2022 10(10)
Imaging standardisation in metastatic colorectal cancer: A joint EORTC-ESOI-ESGAR expert consensus recommendation.
Unterrainer Marcus et al. European journal of cancer (Oxford, England : 1990) 2022 176193-206
Construction of a Colorectal Cancer Prognostic Risk Model and Screening of Prognostic Risk Genes Using Machine-Learning Algorithms.
Du Xuezhi et al. Computational and mathematical methods in medicine 2022 20229408839
Attention-guided sampling for colorectal cancer analysis with digital pathology.
Broad Andrew et al. Journal of pathology informatics 2022 13100110
Using of artificial intelligence: Current and future applications in colorectal cancer screening.
Zacharakis Georgios et al. World journal of gastroenterology 2022 28(24) 2778-2781
CT radiomics identifying non-responders to neoadjuvant chemoradiotherapy among patients with locally advanced rectal cancer.
Zhang Zinan et al. Cancer medicine 2022
Development of prediction model of low anterior resection syndrome for colorectal cancer patients after surgery based on machine-learning technique.
Huang Ming Jun et al. Cancer medicine 2022
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