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Public Health Genomics and Precision Health Knowledge Base (v6.8)
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Genomics and Precision Health Database
Genomics & Health Impact Scan Database|Search|PHGKB
Last data update: Dec 28, 2020
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Supervised machine learning enables non-invasive lesion characterization in primary prostate cancer with [ 68 Ga]Ga-PSMA-11 PET/MRI.
Papp L et al. European journal of nuclear medicine and molecular imaging 2020 Dec
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Advanced analytics and artificial intelligence in gastrointestinal cancer: a systematic review of radiomics predicting response to treatment.
Wesdorp Nina J et al. European journal of nuclear medicine and molecular imaging 2020 Dec
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An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study.
Pantanowitz Liron et al. The Lancet. Digital health 2020 Aug 2(8) e407-e416
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Reproducibility of tumor budding assessment in pancreatic cancer based on a multicenter interobserver study.
Karamitopoulou Eva et al. Virchows Archiv : an international journal of pathology 2020 Dec
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Artificial intelligence (AI) in breast cancer care - Leveraging multidisciplinary skills to improve care.
Cardoso Maria Joao et al. Breast (Edinburgh, Scotland) 2020 Dec
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Artificial intelligence in dentistry: Harnessing big data to predict oral cancer survival.
Hung Man et al. World journal of clinical oncology 2020 Nov 11(11) 918-934
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Quantitative ultrasound radiomics in predicting recurrence for patients with node-positive head-neck squamous cell carcinoma treated with radical radiotherapy.
Dasgupta Archya et al. Cancer medicine 2020 Dec
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The Utility of Deep Learning in Breast Ultrasonic Imaging: A Review.
Fujioka Tomoyuki et al. Diagnostics (Basel, Switzerland) 2020 Dec 10(12)
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Eliminating biasing signals in lung cancer images for prognosis predictions with deep learning.
van Amsterdam W A C et al. NPJ digital medicine 2019 Dec 2(1) 122
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Application of artificial intelligence to the diagnosis and therapy of colorectal cancer.
Wang Yutong et al. American journal of cancer research 2020 10(11) 3575-3598
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A 'Real-Life' Experience on Automated Digital Image Analysis of FGFR2 Immunohistochemistry in Breast Cancer.
Braun Marcin et al. Diagnostics (Basel, Switzerland) 2020 Dec 10(12)
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Artificial intelligence-based imaging analytics and lung cancer diagnostics: Considerations for health system leaders.
Zarzeczny Amy et al. Healthcare management forum 2020 Dec 840470420975062
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Deep convolutional neural networks for multi-planar lung nodule detection: improvement in small nodule identification.
Zheng Sunyi et al. Medical physics 2020 Dec
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Ruling In and Ruling Out COVID-19: Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging and Test Data.
D'Ambrosia Christopher et al. Journal of medical Internet research 2020 Nov
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Combination of a Big Data Analytics Resource System With an Artificial Intelligence Algorithm to Identify Clinically Actionable Radiation Dose Thresholds for Dysphagia in Head and Neck Patients.
Mayo Charles S et al. Advances in radiation oncology 5(6) 1296-1304
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Machine-Learning Radiomics to Predict Early Recurrence in Perihilar Cholangiocarcinoma after Curative Resection.
Qin Huan et al. Liver international : official journal of the International Association for the Study of the Liver 2020 Dec
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Application of Machine Learning for Tumor Growth Inhibition - Overall Survival Modeling Platform.
Chan Phyllis et al. CPT: pharmacometrics & systems pharmacology 2020 Dec
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Putting artificial intelligence (AI) on the spot: machine learning evaluation of pulmonary nodules.
Tandon Yasmeen K et al. Journal of thoracic disease 2020 Nov 12(11) 6954-6965
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Deep Learning-assisted MRI Prediction of Tumor Response to Chemotherapy in Patients with Colorectal Liver Metastases.
Zhu Hai-Bin et al. International journal of cancer 2020 Dec
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Melanoma and Nevus Skin Lesion Classification Using Handcraft and Deep Learning Feature Fusion via Mutual Information Measures.
Almaraz-Damian Jose-Agustin et al. Entropy (Basel, Switzerland) 2020 Apr 22(4)
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Computer-aided diagnosis of esophageal cancer and neoplasms in endoscopic images: a systematic review and meta-analysis of diagnostic test accuracy.
Bang Chang Seok et al. Gastrointestinal endoscopy 2020 Dec
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Analyses of Risk, Racial Disparity, and Outcomes Among US Patients With Cancer and COVID-19 Infection
Q Wang et al, JAMA Oncology, December 10, 2020
Use of Real-World Electronic Health Records to Estimate Risk, Risk Factors, and Disparities for COVID-19 in Patients With Cancer
A Desai et al, JAMA Oncology, December 10, 2020
Prediction of breast cancer distant recurrence using natural language processing and knowledge-guided convolutional neural network.
Wang Hanyin et al. Artificial intelligence in medicine 2020 Nov 110101977
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Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate Cancers.
Oktay Ozan et al. JAMA network open 2020 Nov 3(11) e2027426
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Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study.
Tang Dehua et al. EBioMedicine 2020 Nov 62103146
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Outcome-Oriented Deep Temporal Phenotyping of Disease Progression.
Lee Changhee et al. IEEE transactions on bio-medical engineering 2020 Dec PP
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Prognostic role of artificial intelligence among patients with hepatocellular cancer: A systematic review.
Lai Quirino et al. World journal of gastroenterology 2020 Nov 26(42) 6679-6688
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Development and internal validation of a predictive risk model for anxiety after completion of treatment for early stage breast cancer.
Harris Jenny et al. Journal of patient-reported outcomes 2020 Dec 4(1) 103
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Development and validation of a pancreatic cancer risk model for the general population using electronic health records: An observational study.
Appelbaum Limor et al. European journal of cancer (Oxford, England : 1990) 2020 Dec 14319-30
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Page last reviewed:
Oct 1, 2020
Page last updated:
Dec 28, 2020
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Office of Genomics and Precision Public Health
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