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Precision Health Database


Genomics & Health Impact Scan Database|Search|PHGKB

Last data update: Mar 25, 2023. (Total: 58925 Documents since 2012)
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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
Artificial intelligence-assisted colonoscopy for colorectal cancer screening: a multicenter randomized controlled trial.
Xu Hong et al. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association 2022
Digital image analysis provides robust tissue microenvironment-based prognosticators in stage I-IV colorectal cancer patients.
Jakab Anna et al. Human pathology 2022
A novel AI device for real-time optical characterization of colorectal polyps
C Biffi et al, NPJ Digital Medicine, June 30, 2022
Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer using whole-slide images.
Zhao Ke et al. Precision clinical medicine 2022 4(1) 17-24
Artificial intelligence in gastroenterology and hepatology: how to advance clinical practice while ensuring health equity.
Uche-Anya Eugenia et al. Gut 2022
Multi-Size Deep Learning Based Preoperative Computed Tomography Signature for Prognosis Prediction of Colorectal Cancer.
Li Cheng-Hang et al. Frontiers in genetics 2022 13880093
Current Status and Future Perspectives of Artificial Intelligence in Colonoscopy.
Kamitani Yu et al. Journal of clinical medicine 2022 11(10)
Artificial intelligence-assisted colonoscopy: a narrative review of current data and clinical applications.
Li James Weiquan et al. Singapore medical journal 2022 63(3) 118-124
Power of big data to improve patient care in gastroenterology.
Catlow Jamie et al. Frontline gastroenterology 2022 13(3) 237-244
Swarm learning for decentralized artificial intelligence in cancer histopathology.
Saldanha Oliver Lester et al. Nature medicine 2022
Deep Learning on Histopathological Images for Colorectal Cancer Diagnosis: A Systematic Review.
Davri Athena et al. Diagnostics (Basel, Switzerland) 2022 12(4)
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