研究人员开发了HealthFormer，这是一个生成式多模态Transformer模型，经过海量人体生理学数据训练，用于预测个体健康轨迹。该模型使用来自Human Phenotype Project的数据开发，可以预测疾病和死亡率终点，并在计算机中模拟干预措施。HealthFormer在从个性化营养试验中恢复生物标志物变化以及准确预测已发表研究的干预结果方面显示出潜力，使其成为临床数字孪生的基础。 AI
影响 有望加速个性化医疗和临床数字孪生的发展。
排序理由 这是一篇详细介绍新模型及其能力的学术论文。
AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →
arXiv:2604.27899v1 Announce Type: new Abstract: Understanding how human health changes over time, and why responses to interventions vary between individuals, remains a central challenge in medicine. Here we present HealthFormer, a decoder-only transformer that models the human p…
Understanding how human health changes over time, and why responses to interventions vary between individuals, remains a central challenge in medicine. Here we present HealthFormer, a decoder-only transformer that models the human physiological trajectory generatively, by trainin…
arXiv:2604.24822v1 Announce Type: cross Abstract: Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas of daily life, including health, government, and finance. Recently, transformer…