Analysis of SARS-CoV-2 RNA-Sequences by Interpretable Machine Learning Models T Villman et al, BIORXIV, May 15, 2020

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Last Posted: May 16, 2020

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• Analysis of SARS-CoV-2 RNA-Sequences by Interpretable Machine Learning Models
  T Villman et al, BIORXIV, May 15, 2020
• Opportunistic deep learning of retinal photographs: the window to the body revisited
  SM Waldstein, Lancet Digital Health, May 14, 2020
• Predicting the Growth and Trend of COVID-19 Pandemic using Machine Learning and Cloud Computing
  S Tuli, et al, MEDRXIV, May 11, 2020
• COVID-19 diagnosis prediction by symptoms of tested individuals: a machine learning approach
  Y Zaobi et al, MEDRXIV, May 11, 2020
• A Machine Learning Approach to Management of Heart Failure Populations.
  Jing Linyuan et al. JACC. Heart failure 2020 Apr
• A Review of Statistical and Machine Learning Techniques for Microvascular Complications in Type 2 Diabetes.
  Sambyal Nitigya et al. Current diabetes reviews 2020 May
• Applications of radiomics in precision diagnosis, prognostication and treatment planning of head and neck squamous cell carcinomas.
  Haider Stefan P et al. Cancers of the head & neck 2020 56
• Artificial Intelligence in Cardiology: Present and Future.
  Lopez-Jimenez Francisco et al. Mayo Clinic proceedings 2020 May 95(5) 1015-1039
• Development and validation of phenotype classifiers across multiple sites in the observational health data sciences and informatics network.
  Kashyap Mehr et al. Journal of the American Medical Informatics Association : JAMIA 2020 May
• Evaluation of the accuracy of algorithms to identify soft tissue sarcoma (STS) in administrative claims.
  Princic Nicole et al. Clinical sarcoma research 2020 108

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