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Lung Diseases

- HLBS-PopOmics -

What's New

Last Posted: May 18, 2020

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• The therapeutic potential of exosomes 
  J Madhusoodanan, Nature Outlook, May 13, 2020
• Asthma genetics revisited: understanding disease mechanisms by studying ethnically diverse groups 
  E Melen, Lancet Respiratory Diseases, May 2020
• Screening for chronic obstructive pulmonary disease with artificial intelligence 
  JE Bibault et al, Lancet Digital Health, April 21, 2020
• Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis. 
  Zhong Xue et al. Genetics in medicine : official journal of the American College of Medical Genetics 2020 Apr
• The sticky culprit: Platelets in cystic fibrosis 
  S Sengupta, Sci Trans Med, April 15, 2020
• Deep learning for screening of interstitial lung disease patterns in high-resolution CT images. 
  Agarwala S et al. Clinical radiology 2020 Feb
• Minimal change in structural, functional and inflammatory markers of lung disease in newborn screened infants with cystic fibrosis at one year. 
  Davies Gwyneth et al. Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society 2020 Feb
• Cost-effectiveness analysis of chromosomal microarray as a primary test for prenatal diagnosis in Hong Kong. 
  Chung Claudia Ching Yan et al. BMC pregnancy and childbirth 2020 Feb 20(1) 109
• Trastuzumab Deruxtecan in Previously Treated HER2-Positive Breast Cancer 
  S Modi et al, NEJM, February 12, 2020
• [Italian Cystic Fibrosis Registry (ICFR). Report 2015-2016]. 
  Giordani Barbara et al. Epidemiologia e prevenzione 43(4S1) 1-36
• Applying whole-genome sequencing in relation to phenotype and outcomes in siblings with cystic fibrosis. 
  Wilk Melissa A et al. Cold Spring Harbor molecular case studies 2020 Feb 6(1)
• Clinical Annotation Research Kit (CLARK): Computable Phenotyping Using Machine Learning. 
  Pfaff Emily R et al. JMIR medical informatics 2020 Jan 8(1) e16042
• Deep Learning for Pulmonary Image Analysis: Classification, Detection, and Segmentation. 
  Kido Shoji et al. Advances in experimental medicine and biology 2020 121347-58
• Deep learning-based segmentation of malignant pleural mesothelioma tumor on computed tomography scans: application to scans demonstrating pleural effusion. 
  Gudmundsson Eyjolfur et al. Journal of medical imaging (Bellingham, Wash.) 2020 Jan 7(1) 012705
• Diagnosis of ventilator-associated pneumonia using electronic nose sensor array signals: solutions to improve the application of machine learning in respiratory research. 
  Chen Chung-Yu et al. Respiratory research 2020 Feb 21(1) 45
• Pharmacogenetic investigation of efficacy response to mepolizumab in eosinophilic granulomatosis with polyangiitis. 
  Condreay Lynn D et al. Rheumatology international 2020 Feb
• Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed. 
  Wang Jing et al. Journal of medical Internet research 2020 Jan 22(1) e16816
• Understanding the importance of key risk factors in predicting chronic bronchitic symptoms using a machine learning approach. 
  Deng Huiyu et al. BMC medical research methodology 2019 19(1) 70
• Calling all coronavirus researchers: keep sharing, stay open. 
  et al. Nature 2020 Feb (7793) 7
• Opportunities for machine learning to transform care for people with cystic fibrosis. 
  Abroshan Mahed et al. Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society 2020 Jan 19(1) 6-8