This survey explores the transformative impact of foundation models (FMs) in artificial intelligence, focusing on their integration with federated learning (FL) in biomedical research. Foundation models such as ChatGPT, LLaMa, and CLIP, which are trained on vast datasets through methods including unsup...
[arXiv] Progress and opportunities of foundation models in bioinformatics.[Paper] [arXiv] Large language models in bioinformatics: applications and perspectives.[Paper] [arXiv] Data-centric foundation models in computational healthcare: A survey.[Paper] ...
Large pretrained models have become foundation models leading to breakthroughs in natural language processing and related fields. Developing foundation models for deciphering the ‘languages’ of cells and facilitating biomedical research is promising yet challenging. Here we developed a large pretrained model...
[arXiv] Progress and opportunities of foundation models in bioinformatics.[Paper] [arXiv] Large language models in bioinformatics: applications and perspectives.[Paper] [arXiv] Data-centric foundation models in computational healthcare: A survey.[Paper] ...
The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI) models is likely to usher in newfound capabilities in medicine. We propose a new paradigm for medical AI, which we refer to as generalist medical AI (GMAI). GMAI models will be capable of carrying out ...
In Proc. Advances in Neural Information Processing Systems 33 (eds Larochelle, H. et al.) 1877–1901 (Curran Associates, 2020). Radford, A. et al. Learning transferable visual models from natural language supervision. In Proc. International Conference on Machine Learning 8748–8763 (PMLR, 2021...
Generative pretrained models have achieved remarkable success in various domains such as language and computer vision. Specifically, the combination of large-scale diverse datasets and pretrained transformers has emerged as a promising approach for developing foundation models. Drawing parallels between languag...
Computational tumor purity is calculated by fitting the observed log-ratio and minor allele frequency data with statistical models that predict a genome-wide copy number profile, tumor ploidy, and tumor purity (i.e., computational tumor purity). The log-ratio profile is obtained by normalizing ...
These findings represent the transformative potential of medical foundation models to unlock the role of artificial intelligence in the care of patients with cancer.doi:10.1038/s41586-024-08169-3Kondepudi, AkhilComputational Medicine and Bioinformatics, University of Michigan, Ann Arbor, USAPekmezci, ...
By integrating visual and linguistic understanding, visual–language foundation models (VLFMs) have the great potential to advance the interpretation of medical data, thereby enhancing diagnostic precision, treatment planning, and patient management. We reviewed the developmental strategies of VLFMs, detaili...