Detecting tumor infiltration during surgery has been a vital concern for over a century. Despite advances in healthcare, the ...

In another triumph for AI in healthcare, researchers have developed a model that can spot bits of brain tumors that surgeons ...

Researchers have developed an AI-powered model that—in 10 seconds—can determine during surgery if any part of a cancerous ...

Researchers have developed an AI powered model that -- in 10 seconds -- can determine during surgery if any part of a ...

AI model FastGlioma detects residual brain tumors in 10 seconds with 92% accuracy, offering real-time guidance to improve ...

FastGlioma, an AI-powered model developed by University of Michigan and UCSF researchers, can detect residual brain tumors in ...

The AI, called FastGlioma, calculated how much residual brain cancer remained following surgery with approximately 92% ...

为了解决这一问题，密歇根大学与加州大学旧金山分校的研究团队开发了一款名为 FastGlioma 的人工智能诊断工具。这一创新技术能在手术中实时提供诊断信息，帮助外科医生在数秒内识别和切除脑 肿瘤 。

引言在脑胶质瘤的手术治疗中，如何精确检测和识别肿瘤的浸润边界一直是一个极具挑战性的难题。尽管现代手术工具在不断进步，但大多数胶质瘤患者在手术后仍会残留一些无法完全切除的肿瘤组织。这不仅增加了复发的风险，还对患者的生存率和生活质量造成严重影响。为了解决 ...

美国密歇根大学和加利福尼亚大学旧金山分校领导的研究人员开发出一款名为FastGlioma的人工智能（AI）模型。在脑手术中，该模型仅用10秒就判断出是否还有残留的癌性肿瘤。在识别肿瘤残留方面，FastGlioma的表现远超传统方法，有望给神经外科领域带来变革。研究成果发表在最新一期《自然》杂志上。

美国科学家近日在《自然》杂志发表重大研究成果:由密歇根大学和加州大学旧金山分校联合开发的人工智能模型FastGlioma，可在脑瘤手术中实现10秒内快速判断癌性肿瘤残留，为神经外科手术带来革命性突破。

The breakthrough technology, named FastGlioma, was introduced in a research paper titled "Foundation models for fast, ...