AIM study highlighted by MGB News and several outlets - ScienceMag, Science Daily and ecancer.
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Researchers at AIM investigated the use of LLMs for patient portal messaging.
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AIM Researchers build foundation model to discover new cancer imaging biomarkers
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AIM study investigates if AI can highlight social determinants of health from clinical notes
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AIM investigators developed AI to track muscle mass for children through young adulthood
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Bloomberg, WBUR, Yahoo and many other major news outlets feature AIM study on ChatGPT
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AIM researchers investigate ChatGPT for its ability to provide cancer treatment recommendations
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PLOS Medicine’s top 10% cited included AIM study on deep learning for lung cancer prognostication
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In Nature Comm, AIM scientists show that AI applied to X-rays can be used as a new biomarker source in cancer.
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AIM investigators published a clinical evaluation of AI algorithms to screen for extranodal-extension on CT.
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In Nature Medicine, AIM and TRACERx investigators show the importance of AI-based body composition.
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A recent publication validated a lung cancer prediction model in 14,737 patients from Mass General Brigham.
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The Moning Show at CNN features our new study predicting cardiovascular risk from x-rays.
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We developed an AI model that can accurately predict distant metastases after treatment for lung cancer patients.
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In Lancet Digital Health, we published a clinical validation of deep learning algorithms to target lung cancer tumors.
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The NIH awards the ModelHub platform for reproducible AI research.
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Web of Science awards AIM researcher as among the top highest cited scientists worldwide.
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Together with the WHO we defined a framework for the global application of AI-based Medical Devices.
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In this paper we demonstrate that deep learning applied to x-rays can be used as a new biomarker source.
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In Cancer Cell, we published our perspective on the impact of AI in Clinical Oncology.
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