Mashup Score:252
NatureSelf-supervised learning in medicine and healthcare – Nature Biomedical Engineering - 5 days
Mashup Score:252
# AI
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Cancer CellPan-cancer integrative histology-genomic analysis via multimodal deep learning - 1 week
Mashup Score:227
Chen et al. present a pan-cancer analysis that uses deep learning to integrate whole-slide pathology images and molecular features to predict cancer prognosis, with multimodal...
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Multimodal #AI for cancer: integrated deep learning of histology and genomics in 14 cancer types to sharpen prognosis at the individual level. An #OpenScience resource https://t.co/sg9N894kg3 @Cancer_Cell @AI4Pathology @richardjchen @DFKW_MD @BWHPath @broadinstitute https://t.co/sg9N894kg3 - view on twitter
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MIT Technology ReviewAI is learning how to create itself - 5 days
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Humans have struggled to make truly intelligent machines. Maybe we need to let them get on with it...
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RT @baski_LA: Artificial intelligence might not need us to become more intelligent than we are via @techreview #AI https://t.co/YqjTOMpR6q… - view on twitter
More coverage:
#ai
Mashup Score:27
LancetThe Lancet Gastroenterology and Hepatology: Homepage - 1 week
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Discover articles from The Lancet Gastroenterology & Hepatology, providing a clear, independent perspective about the clinical advances and practice-changing research shaping your specialty...
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RT @LancetGastroHep: Our September issue is out NOW at https://t.co/PqPBcCqeLY — we have content on optimising trial designs for #AI in #en… - view on twitter
More coverage:
#ai
Mashup Score:23
GastroenterologyArtificial intelligence can detect pancreas cancer on computed tomography well before its detection by radiologists and before the onset of cancer symptoms when surgical...
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From @MayoClinic in @AGA_Gastro: Radiomics-Based Machine-Learning Models Can Detect #PancreaticCancer on Prediagnostic CTs at a Substantial Lead Time Prior to Clinical Diagnosis https://t.co/V7FaEfPere Can we reduce the portion of “missed cancers” using #AI? https://t.co/V7FaEfPere - view on twitter
Mashup Score:20
OUP Academicfar-reaching beneficial effects of sodium–glucose co-transporter 2 inhibitors in heart failure - 1 day
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With thanks to Amelia Meier-Batschelet, Johanna Huggler, and Martin Meyer for help with compilation of this...
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EHJ issue 43-31 out now! Read this EHJ issue on the far-reaching beneficial effects of sGLT2i in HF and on AI-based prediction models https://t.co/NzRpzgjwVz @escardio @ESC_Journals #cardiotwitter #EHJ #artificialintelligence #AI #machinelearning https://t.co/NzRpzgjwVz - view on twitter
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Robotics & Automation NewsBeyond Imagination receives order for 1,000 humanoid robots - 1 week
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Robotics innovator Beyond Imagination has entered into an agreement with SELF Labs to provide at least 1,000 humanoid robots for use in agricultural “grow...
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RT @EvanKirstel: Beyond Imagination receives order for 1,000 humanoid robots https://t.co/89QbZtb1uV #iot #AI #Robotics https://t.co/89QbZtb1uV - view on twitter
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LinkedinConversational AI In The Coming Years - 6 days
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Conversational AI is something that is encroaching into people’s lives every day. Every industry is taking a look at what this type of AI...
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Check out the latest article in my newsletter: Conversational AI In The Coming Years by @EvanKirstel https://t.co/an5DoIEYAp via @LinkedIn #AI #NLP #CX #CCTR #EX https://t.co/an5DoIEYAp - view on twitter
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reddit1 vote and 3 comments so far on...
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Using various plastic devices for 3D printing in the abdominal cavity is safe has been experimentally proven #MedTwitterAI #3D #botpenguin #chatbots #AI #healthbot #botmd #sminaev #doctors https://t.co/eRv1TESOv0 - view on twitter
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Neuroscience NewsWhen It Comes to AI, Can We Ditch the Datasets? – Neuroscience News - 2 days
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Training a machine learning algorithm with synthetic data for image classification can rival one trained on traditional...
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RT @ipfconline1: When It Comes to #AI, Can We Ditch the Datasets? https://t.co/LRa0G9mfXU via @neurosciencenew #DataScience Cc @MarshaC… - view on twitter
This Review discusses the advantages and limitations of self-supervised methods and models for use in medicine and healthcare, and the challenges in collecting unbiased...
Until now, most #AI in medicine has involved large annotated datasets for inputs, known as supervised deep learning. Next up is self-supervised learning. @RayanKrishnan @pranavrajpurkar and I review this topic @natBME https://t.co/5Uyrc8rX4m https://t.co/5Uyrc8rX4m - view on twitter