Google’s AI Research in Healthcare: Med-PaLM and Beyond
Published: 2024-05-29 11:36:47

## Introduction

Artificial Intelligence (AI) has been making significant strides in various sectors, and healthcare is no exception. Google's AI research, particularly in the medical domain, has been groundbreaking. This blog delves into Google's advancements in healthcare AI, focusing on their medical large language model (LLM) research, including Med-PaLM and its successor Med-PaLM 2.

## Med-PaLM: A Revolutionary AI Model

### The Genesis of Med-PaLM

Med-PaLM is a large language model (LLM) designed to provide high-quality answers to medical questions. It harnesses the power of Google's large language models, which have been aligned to the medical domain and evaluated using medical exams, medical research, and consumer queries. Learn more.

### Med-PaLM 2: The Next Iteration

Med-PaLM 2, introduced at Google Health’s annual event, The Check Up, in March 2023, was the first to reach human expert level on answering USMLE-style questions. According to physicians, the model's long-form answers to consumer medical questions improved substantially. Read more.

## AI in Ultrasound Image Interpretation

### Bridging the Gap in Maternal Care

In recent years, sensor technology has evolved to make ultrasound devices more affordable and portable. However, they often require experts with years of experience to conduct exams and interpret the images. To help bridge this divide, Google is building AI models that can help simplify acquiring and interpreting ultrasound images to identify important information like gestational age in expecting mothers and early detection of breast cancer. Learn more.

### Partnerships for Real-World Applications

Google is partnering with Jacaranda Health, a Kenya-based nonprofit focused on improving health outcomes for mothers and babies in government hospitals, to research digital solutions that can help them reach their goal. In Sub-Saharan Africa, maternal mortality remains high, and there is a shortage of workers trained to operate traditional high-cost ultrasound machines. Read more.

## Enhancing Radiotherapy Planning with AI

### Collaboration with Mayo Clinic

Over the past three years, Google has partnered with Mayo Clinic to explore how AI can support the tedious, time-consuming process of planning for radiotherapy, a common cancer treatment used to treat more than half of cancers in the U.S. The most labor-intensive step in the planning process is a technique called “contouring”, where clinicians draw lines on CT scans to separate areas of cancer from nearby healthy tissues that can be damaged by radiation during treatment. Learn more.

### Future Research and Development

Google will soon publish research about the findings of their study and the radiotherapy model they developed. As of today, they are formalizing their agreement with Mayo Clinic to explore further research, model development, and commercialization. Read more.

## AI for Tuberculosis Screening

### Addressing Global Health Challenges

Building on years of health AI research, Google is working with partners on the ground to bring the results of their research on tuberculosis (TB) AI-powered chest x-ray screening into the care setting. According to the WHO, TB is the ninth leading cause of death worldwide, with over 25% of TB deaths occurring in Africa. Learn more.

### Real-World Implementation

While TB is treatable, it requires cost-effective screening solutions to help catch the disease early and reduce community spread. Google's AI models aim to provide these solutions, making a significant impact on global health. Read more.

## Conclusion

Google's advancements in AI for healthcare, particularly through their Med-PaLM models, are paving the way for more accurate, efficient, and accessible medical care. From improving maternal care and cancer treatments to addressing global health challenges like tuberculosis, Google's AI research is making a significant impact on the healthcare industry. Learn more.

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