We developed several heart segmentation algorithms that work on gated and non-gated CT scans.
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Scientific American discusses the hype in AI and highlights study from AIM.
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AIM investigators describe their view on AI reproducibility and transparency.
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An automated deep-learning approach based on chest x-rays can improve lung cancer screening.
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In The Lancet Digital Health, AIM investigators have defined the levels of autonomy in medical AI.
Read MoreIn Nature Reviews Clinical Oncology, we highlight how AI is transforming the field of radiation oncology to treat patients more accurately and efficiently.
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Science Magazine published our perspective on the application of Artificial intelligence in resource-poor health care settings.
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At the annual meeting, a study about AI for cardiovascular risk prediction was awarded.
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Our article "Deep learning for lung cancer prognostication" was selected by IMIA as one of the best articles of the year.
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JAMA Network Open published our study about using deep learning to extract prognostic information from chest radiographs
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In a news item, Science Magazine discusses the positives and negatives of AI in medicine.
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JAMA Oncology published our investigation of deep learning methods for lung tumor segmentation.
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Clinical Cancer Research published about deep learning applied to serial imaging to improve outcome predictions.
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At their annual meeting, the AACR awarded an AIM article as it was the most-cited.
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We used AI to quantify the radiographic phenotype of a tumor to predict IO response.
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Our publication about artificial intelligence in cancer imaging was highlighted on the cover of CA: A Cancer Journal for clinicians.
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JNCI published our study about trial design of novel technologies for cancer treatment, including artificial intelligence algorithms.
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A review of AI applications in the imaging of several tumor types has been published in CA: A Cancer Journal for clinicians.
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AIM’s publication “AI in Radiology” was featured in the Nature about promising technologies transforming the world.
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Our publication “Artificial Intelligence in Radiology” was highlighted on the cover of Nature Reviews Cancer.
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