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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.
Medical model is the term coined by psychiatrist R. D. Laing in his The Politics of the Family and Other Essays (1971), for the "set of procedures in which all doctors are trained". [1] It includes complaint, history, physical examination, ancillary tests if needed, diagnosis, treatment, and prognosis with and without treatment.
The Stanford Institute for Human-Centered Artificial Intelligence's (HAI) Center for Research on Foundation Models (CRFM) coined the term "foundation model" in August 2021 [16] to mean "any model that is trained on broad data (generally using self-supervision at scale) that can be adapted (e.g., fine-tuned) to a wide range of downstream tasks". [17]
Generative Pre-trained Transformer 2 (GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages. [2] It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019. [3] [4] [5]
While the fine-tuning was adapted to specific tasks, its pre-training was not; to perform the various tasks, minimal changes were performed to its underlying task-agnostic model architecture. [3] Despite this, GPT-1 still improved on previous benchmarks in several language processing tasks, outperforming discriminatively-trained models with ...
In 2018, Banerjee et al. [9] proposed a deep learning model for estimating short-term life expectancy (>3 months) of the patients by analyzing free-text clinical notes in the electronic medical record, while maintaining the temporal visit sequence. The model was trained on a large dataset (10,293 patients) and validated on a separated dataset ...
Isogenic human disease models are a family of cells that are selected or engineered to accurately model the genetics of a specific patient population, in vitro.They are provided with a genetically matched 'normal cell' to provide an isogenic system to research disease biology and novel therapeutic agents. [1]
Generative Pre-trained Transformer 3 (GPT-3) is a large language model released by OpenAI in 2020.. Like its predecessor, GPT-2, it is a decoder-only [2] transformer model of deep neural network, which supersedes recurrence and convolution-based architectures with a technique known as "attention". [3]