User profiles for M.P. Lungren
 | Matthew LungrenChief Data Science Officer Microsoft HLS, Associate Professor UCSF, Adjunct Professor … Verified email at stanford.edu Cited by 17428 |
The current and future state of AI interpretation of medical images
P Rajpurkar, MP Lungren - New England Journal of Medicine, 2023 - Mass Medical Soc
The Current and Future State of AI Interpretation of Medical Images | NEJM Skip to main content
NEJM Group Follow Us Facebook Twitter Instagram YouTube LinkedIn Prepare to become a …
NEJM Group Follow Us Facebook Twitter Instagram YouTube LinkedIn Prepare to become a …
Preparing medical imaging data for machine learning
Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The
potential applications are vast and include the entirety of the medical imaging life cycle from …
potential applications are vast and include the entirety of the medical imaging life cycle from …
[HTML][HTML] Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines
Advancements in deep learning techniques carry the potential to make significant contributions
to healthcare, particularly in fields that utilize medical imaging for diagnosis, prognosis, …
to healthcare, particularly in fields that utilize medical imaging for diagnosis, prognosis, …
Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning
We develop an algorithm that can detect pneumonia from chest X-rays at a level exceeding
practicing radiologists. Our algorithm, CheXNet, is a 121-layer convolutional neural network …
practicing radiologists. Our algorithm, CheXNet, is a 121-layer convolutional neural network …
Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison
…, DB Larson, CP Langlotz, BN Patel, MP Lungren… - Proceedings of the AAAI …, 2019 - aaai.org
Large, labeled datasets have driven deep learning methods to achieve expert-level
performance on a variety of medical imaging tasks. We present CheXpert, a large dataset that …
performance on a variety of medical imaging tasks. We present CheXpert, a large dataset that …
[HTML][HTML] Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
Background Chest radiograph interpretation is critical for the detection of thoracic diseases,
including tuberculosis and lung cancer, which affect millions of people worldwide each year. …
including tuberculosis and lung cancer, which affect millions of people worldwide each year. …
[HTML][HTML] AI recognition of patient race in medical imaging: a modelling study
Background Previous studies in medical imaging have shown disparate abilities of artificial
intelligence (AI) to detect a person's race, yet there is no known correlation for race on …
intelligence (AI) to detect a person's race, yet there is no known correlation for race on …
[HTML][HTML] MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports
…, SJ Berkowitz, NR Greenbaum, MP Lungren… - Scientific data, 2019 - nature.com
Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection
of a patient’s chest, but requires specialized training for proper interpretation. With the …
of a patient’s chest, but requires specialized training for proper interpretation. With the …
MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs
…, TJ Pollard, NR Greenbaum, MP Lungren… - arXiv preprint arXiv …, 2019 - arxiv.org
Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection
of a patient's thorax, but requiring specialized training for proper interpretation. With the …
of a patient's thorax, but requiring specialized training for proper interpretation. With the …
[HTML][HTML] Deep-learning-assisted diagnosis for knee magnetic resonance imaging: development and retrospective validation of MRNet
Background Magnetic resonance imaging (MRI) of the knee is the preferred method for
diagnosing knee injuries. However, interpretation of knee MRI is time-intensive and subject to …
diagnosing knee injuries. However, interpretation of knee MRI is time-intensive and subject to …