A foundation model for chest radiography
ARK is a chest radiography foundation model reported in Nature Machine Intelligence for visual representation learning and radiology downstream tasks.
10 条结果
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Toward expert-level medical question answering with large language models
Nature Medicine paper on Med-PaLM 2 and expert-level medical question answering with large language models.
A generalist vision-language foundation model for diverse biomedical tasks
Nature Medicine article describing a generalist biomedical vision-language foundation model evaluated across multiple biomedical tasks.
A whole-slide foundation model for digital pathology from real-world data
Prov-GigaPath is a pathology foundation model trained on real-world whole-slide images and released with a Nature paper and project resources.
Segment anything in medical images
MedSAM adapts the Segment Anything paradigm to medical image segmentation and reports broad evaluation across imaging modalities.
Towards generalist biomedical AI
Med-PaLM Multimodal evaluates a generalist biomedical AI system across medical question answering, imaging, report generation, and multimodal tasks.
Ark+: Supervised training a single high-performance AI foundation model from many differently labeled datasets-no label consolidation required
一种面向多源异构标注数据的监督训练方法，用于训练单一高性能 AI 基础模型，避免人工标签整合。
An Electrocardiogram Foundation Model Built on over 10 Million Recordings
NEJM AI 论文，报道基于超过 1000 万条 ECG 记录构建的心电图基础模型。
A foundation model for human-AI collaboration in medical literature mining
Nature Communications 论文，提出用于医学文献挖掘的人机协作基础模型。
Human–large language model collaboration in clinical medicine: a systematic review and meta-analysis
系统综述与荟萃分析，评估临床医学中人类与大语言模型协作相对于人类单独工作流的表现，覆盖临床推理、文档和解释等任务；研究指出当前证据仍初步且具有情境依赖性，建议后续开展预注册、务实、多中心并嵌入真实工作流的临床研究。