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  "author": "Sivaramakrishnan Rajaraman",
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  "author": "Sivaramakrishnan Rajaraman",
            
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  "extra_authors": [
            
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    {
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      "extra_author": "Feng Yang",
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      "extra_author": "Feng Yang",
            
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      "extra_author": "Ghada Zamzmi",
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    {
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      "extra_author": "Peng Guo",
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    },
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      "extra_author": "Zhiyun Xue",
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      "extra_author": "Zhiyun Xue",
            
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    },
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    {
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      "extra_author": "Sameer K Antani",
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      "extra_author": "Sameer K Antani",
            
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  "name": 
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gmenting-tuberculosis-consistent-manifestations-in-chest-radiographs",
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gmenting-tuberculosis-consistent-manifestations-in-chest-radiographs",
            
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  "notes": "Automated segmentation of tuberculosis (TB)-consistent 
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  "notes": "Automated segmentation of tuberculosis (TB)-consistent 
            
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lesions in chest X-rays (CXRs) using deep learning (DL) methods can 
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lesions in chest X-rays (CXRs) using deep learning (DL) methods can 
            
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help reduce radiologist effort, supplement clinical decision-making, 
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help reduce radiologist effort, supplement clinical decision-making, 
            
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and potentially result in improved patient treatment.",
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and potentially result in improved patient treatment.",
            
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  "title": "Deep ensemble learning for segmenting 
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  "title": "Deep ensemble learning for segmenting 
            
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tuberculosis-consistent manifestations in chest radiographs",
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tuberculosis-consistent manifestations in chest radiographs",
            
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}
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}