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Epi Info is public domain statistical software for epidemiology developed by Centers for Disease Control and Prevention. [1]Spatiotemporal Epidemiological Modeler is a tool, originally developed at IBM Research, for modelings and visualizing the spread of infectious diseases.
National Survey on Drug Use and Health Large scale survey on health and drug use in the United States. None. 55,268 Text Classification, regression 2012 [269] United States Department of Health and Human Services: Lung Cancer Dataset Lung cancer dataset without attribute definitions 56 features are given for each case 32 Text Classification 1992
A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are often examples of foundation models.
IHME model – Institute for Health Metrics and Evaluation COVID model; MEmilio [35] – an open source high performance Modular EpideMIcs simuLatIOn software based on hybrid graph-SIR-type model [36] with commuter testing between regions [37] and vaccination strategies [38] and agent-based models
Greater health data lays the groundwork for the implementation of AI algorithms. A large part of industry focus of implementation of AI in the healthcare sector is in the clinical decision support systems. As more data is collected, machine learning algorithms adapt and allow for more robust responses and solutions. [111]
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
These models have been applied in the context of question answering (QA) where the long-term memory effectively acts as a (dynamic) knowledge base and the output is a textual response. [ 75 ] In sparse distributed memory or hierarchical temporal memory , the patterns encoded by neural networks are used as addresses for content-addressable ...
[1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text. T5 models are usually pretrained on a massive dataset of text and code, after which they can perform the text-based tasks that are similar to their pretrained tasks.
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