Katie Shpanskaya
Duke University(US)
Publications by Year
Research Areas
Radiomics and Machine Learning in Medical Imaging, Alzheimer's disease research and treatments, COVID-19 diagnosis using AI, Lung Cancer Diagnosis and Treatment, Dementia and Cognitive Impairment Research
Most-Cited Works
- → CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep\n Learning(2017)1,447 cited
- → Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists(2018)1,330 cited
- → Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet(2018)709 cited
- → CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison(2019)391 cited
- → Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model(2019)257 cited
- → MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs(2017)248 cited
- → PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging(2020)177 cited
- → Sex Differences in Cognitive Decline in Subjects with High Likelihood of Mild Cognitive Impairment due to Alzheimer’s disease(2018)159 cited
- → MR Imaging–Based Radiomic Signatures of Distinct Molecular Subgroups of Medulloblastoma(2018)126 cited