Large language models (LLMs) have achieved unprecedented accuracy on medical question-answering benchmarks, showcasing their potential to revolutionize healthcare by supporting clinicians and patients. However, these benchmarks often fail to capture the full complexity of real-world medical scenarios. To truly harness…
To the untrained eye, a medical image like an MRI or X-ray appears to be a murky collection of black-and-white blobs. It can be a struggle to decipher where one structure (like a tumor) ends and another begins. When trained…
GraphRAG uses large language models (LLMs) to create a comprehensive knowledge graph that details entities and their relationships from any collection of text documents. This graph enables GraphRAG to leverage the semantic structure of the data and generate responses to…
Inventors and researchers have been developing robots for almost 70 years. To date, all the machines they have built — whether for factories or elsewhere — have had one thing in common: they are powered by motors, a technology that…
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In this article, we will explore the Phi-3 model from the official technical report published by Microsoft. Figure 1. Phi-3 family of models (source: ). Language models, especially the Small Langauge Models (SLMs) have come a long way in the…
Dealing with massive amounts of data is not always straightforward. Often, a data scientist needs to trim down a large data table into a handful of key components that can be used for further analysis. For example, we may want…
VirtualMultiplexer architecture The VirtualMultiplexer is a generative AI toolkit that performs unpaired H&E-to-IHC translation. An overview of the model’s architecture is shown in Fig. 2a. The VirtualMultiplexer is trained using two sets of images: source H&E images, denoted as \({X}_{{\rm{img}}}=\{x\in…
To validate the proposed models, we employed two multi-lead electrocardiogram datasets mentioned in Sect. 4.1. Baseline models referenced in Sect. 4.2 and state-of-the-art models were utilized for comparison, juxtaposed with STFAC-ECGNet. Results of PTB-XL dataset Table 2 presents the measurement results of…
Deephaven is a powerful analytics engine that makes processing large data more intuitive than ever. Iceberg is a table format that provides fast, efficient, and scalable data storage. Combining the two is like bringing Holmes and Watson together to solve…
[TEASER ENDS] GRETCHEN HUIZINGA: You’re listening to Collaborators, a Microsoft Research Podcast showcasing the range of expertise that goes into transforming mind-blowing ideas into world-changing technologies. I’m Dr. Gretchen Huizinga. [MUSIC FADES] Today I’m talking to Dr. Richard Black, a…
Kwakkel, G., Kollen, B. J., van der Grond, J. & Prevo, A. J. Probability of regaining dexterity in the flaccid upper limb: Impact of severity of paresis and time since onset in acute stroke. Stroke 34(9), 2181–2186 (2003). Article PubMed …