What You Should Know:

您應該知道：

– Google has introduced Health AI Developer Foundations (HAI-DEF), a public resource designed to empower developers in building and implementing AI models for healthcare more efficiently.

–谷歌推出了健康A(chǔ)I開發(fā)者基金會（HAI-DEF），這是一種公共資源，旨在幫助開發(fā)者更有效地構(gòu)建和實施醫(yī)療保健AI模型。

– The initiative aims to democratize AI development in the healthcare sector, fostering innovation and improving patient care.

–該倡議旨在使醫(yī)療保健領(lǐng)域的人工智能發(fā)展民主化，促進創(chuàng)新并改善患者護理。

Addressing Challenges in Healthcare AI Development

解決醫(yī)療保健AI開發(fā)中的挑戰(zhàn)

Developing AI for healthcare presents unique challenges:

為醫(yī)療保健開發(fā)人工智能面臨著獨特的挑戰(zhàn)：

Data Requirements: Large, diverse datasets are crucial for training robust and generalizable AI models.Expertise: Specialized knowledge in both AI and healthcare is essential.Computational Resources: Training and deploying sophisticated AI models require significant computational power.

數(shù)據(jù)要求：大型多樣的數(shù)據(jù)集對于訓練健壯且可推廣的AI模型至關(guān)重要。專業(yè)知識：人工智能和醫(yī)療保健方面的專業(yè)知識至關(guān)重要。計算資源：訓練和部署復雜的人工智能模型需要強大的計算能力。

These barriers can hinder innovation and limit the development of AI solutions for diverse healthcare needs.

這些障礙可能會阻礙創(chuàng)新，并限制針對不同醫(yī)療保健需求的人工智能解決方案的開發(fā)。

Introducing HAI-DEF

HAI-DEF簡介

HAI-DEF provides developers with open-weight models, instructional Colab notebooks, and comprehensive documentation to support every stage of AI development, from research to commercialization. This resource aims to:

HAI-DEF為開發(fā)人員提供了開放權(quán)重模型、教學Colab筆記本和全面的文檔，以支持AI開發(fā)的每個階段，從研究到商業(yè)化。該資源旨在：

Improve efficiency: Streamline the process of building and deploying healthcare AI models.Reduce barriers to entry: Enable a wider range of developers to contribute to healthcare AI innovation.Promote diverse applications: Support the development of AI solutions for various healthcare needs.

提高效率：簡化構(gòu)建和部署醫(yī)療保健AI模型的過程。。促進多樣化應用：支持針對各種醫(yī)療保健需求開發(fā)人工智能解決方案。

HAI-DEF’s Inaugural Models

HAI-DEF的首款車型

The initial release of HAI-DEF includes three specialized embedding models for medical imaging:

HAI-DEF的初始版本包括三種用于醫(yī)學成像的專用嵌入模型：

CXR Foundation: For chest X-rays.Derm Foundation: For skin images.Path Foundation: For digital pathology.

CXR基金會：用于胸部X光檢查。真皮基礎(chǔ)：用于皮膚圖像。Path基礎(chǔ)：數(shù)字病理學。

These models are pre-trained on large, diverse datasets and can be fine-tuned for specific use cases, enabling developers to build high-performing AI applications with reduced data and computational requirements.

這些模型是在大型、多樣的數(shù)據(jù)集上預先訓練的，可以針對特定的用例進行微調(diào)，使開發(fā)人員能夠以減少的數(shù)據(jù)和計算需求構(gòu)建高性能的AI應用程序。

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網(wǎng)址: 谷歌啟動健康人工智能開發(fā)者基金會（HAI http://m.u1s5d6.cn/newsview810345.html