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Precision therapeutics require multimodal adaptive models that generate personalized treatment recommendations.
Openfda: an innovative platform providing access to a wealth of fda’s publicly available data
Kass-Hout, T. A · 2016
Earlier work this paper cites.
Practice guideline update summary: Corticosteroid treatment of duchenne muscular dystrophy
Gloss, D., Moxley, R. T. I., Ashwal, S. & Oskoui, M · 2016
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Attention is all you need
Vaswani, A · 2017
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Automatic differentiation in pytorch
Paszke, A · 2017
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Improving language understanding by generative pre-training (2018)
Radford, A., Narasimhan, K., Salimans, T., Sutskever, I · 2018
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Lewis, P · 2020
Earlier work this paper cites.
Language models are few-shot learners
Brown, T · 2020
Earlier work this paper cites.
Trl: Transformer reinforcement learning
von Werra, L · 2020
Earlier work this paper cites.
Transformers: State-of-the-art natural language processing
Wolf, T · 2020
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Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
Rasley, J., Rajbhandari, S., Ruwase, O. & He, Y · 2020
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Antisense oligonucleotide-mediated exon-skipping therapies: precision medicine spreading from duchenne muscular dystrophy
Matsuo, M · 2021
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Lora: Low-rank adaptation of large language models
Hu, E. J · 2021
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Jiang, A. Q · 2023
Earlier work this paper cites.
Llama: Open and efficient foundation language models
Touvron, H · 2023
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Bai, J · 2023
Earlier work this paper cites.
Large language models encode clinical knowledge
Singhal, K · 2023
Cited alongside, same era.
Meditron-70b: Scaling medical pretraining for large language models
Chen, Z · 2023
Cited alongside, same era.
Retrieval-augmented generation for large language models: A survey
Gao, Y · 2023
Cited alongside, same era.
Autonomous chemical research with large language models
Boiko, D. A., MacKnight, R., Kline, B. & Gomes, G · 2023
Cited alongside, same era.
React: Synergizing reasoning and acting in language models
Yao, S · 2023
Cited alongside, same era.
Chemcrow: Augmenting large-language models with chemistry tools
The virtual lab: Ai agents design new sars-cov-2 nanobodies with experimental validation
Swanson, K., Wu, W., Bulaong, N. L., Pak, J. E. & Zou, J · 2024
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The human phenotype ontology in 2024: phenotypes around the world
Castellanos, F · 2024
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Gpt-4o (2024)
OpenAI · 2024
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Language models are surprisingly fragile to drug names in biomedical benchmarks
Gallifant, J · 2024
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Clinicalbench: Can llms beat traditional ml models in clinical prediction?
Chen, C · 2024
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Gorilla openfunctions v2 (2024)
Ji, C. C.-J · 2024
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Bran, A. M · 2023
Cited alongside, same era.
The next-generation open targets platform: reimagined, redesigned, rebuilt
Ochoa, D · 2023
Cited alongside, same era.
Building a knowledge graph to enable precision medicine
Chandak, P., Huang, K. & Zitnik, M · 2023
Cited alongside, same era.
Towards general text embeddings with multi-stage contrastive learning
Li, Z · 2023
Cited alongside, same era.
A foundation model for clinician-centered drug repurposing
Huang, K · 2024
Cited alongside, same era.
Dubey, A · 2024
Cited alongside, same era.
Berkeley function calling leaderboard
Yan, F · 2024
Cited alongside, same era.
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Introducing openai o1-preview (2024)
OpenAI · 2024
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openfda (2024)
U.S. Food and Drug Administration · 2024
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24.09 platform release now live
Targets, O · 2024
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Toward expert-level medical question answering with large language models
Singhal, K · 2025
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Medical large language models are vulnerable to data-poisoning attacks
Alber, D. A · 2025
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watt-tool-8b: A fine-tuned language model for tool usage and multi-turn dialogue
Dadao, I · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Guo, D · 2025
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Multimodal medical code tokenizer
Su, X · 2025
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