Baidu acquires GBI Health, where will the popular "AI + medical" go?

# During this period, the medical industry has been a hot topic. First, the popularity of ChatGPT spread from the "search field" to the "medical field", triggering hot topics such as "Can ChatGPT subvert medical AI" and "How long will it take for ChatGPT to be used for medical consultation"; then Baidu acquired the world's leading one-stop medical service GBI, an information data provider, opens a new era of "AI medical big data intelligent full-chain insights". After the merger is completed, Baidu is very likely to combine Wen Xinyiyan with GBI, which has massive medical and device data. This move will also bring Baidu corresponding influence in the field of medical business solution services. What are the core application scenarios of "AI medical care" that have triggered heated discussions? What are the development prospects? Finding the answer to the question starts with the development of the AI ​​medical market.

"AI Medical" is on fire

Baidu acquired GBI and combined Wen Xinyiyan with GBI, setting off a wave of "AI Medical". This shows that the participation of artificial intelligence in all aspects of the medical industry is gradually deepening. According to survey data from market research company ReportLinker, the global healthcare AI market will grow from US$14.6 billion in 2023 to US$102.7 billion in 2028, with a compound annual growth rate of 47.6%. At the same time, AI’s help to medical staff is being recognized. In the "Future Doctor White Paper" survey, 80% of the world's medical staff surveyed said that big data will be deeply integrated into work and diagnosis and treatment processes, helping doctors to formulate more accurate diagnosis and treatment plans and improve decision-making efficiency.

The deep integration of AI and the medical industry first began in the mid-to-late 20th century. Artificial intelligence begins to help doctors obtain authoritative medical information, thereby realizing a clinical diagnosis and treatment knowledge base for auxiliary diagnosis. In the early 21st century, humans began to gradually explore the relationship between artificial intelligence technology and intelligent robots, finally allowing surgical robots to be applied in the field of auxiliary medical care. It was also in the early 21st century that the United States also began to try to sign relevant bills to encourage additional financial support for hospitals that use electronic medical records. Until 2014, the development of artificial intelligence technology gradually entered the vertical segmentation field, and artificial intelligence companies began to target the impact of AI.

In recent years, thanks to the improvement in image recognition accuracy of artificial intelligence in the medical field, AI imaging has become popular and is considered to be one of the areas where artificial intelligence is most likely to be implemented. At the same time, the clinical diagnosis and treatment knowledge base that humans have cultivated for many years has allowed a series of products including clinical auxiliary decision support systems to be promoted and gradually mature. Not only that, AI has also begun to penetrate into patients' digital medical record management systems. While solving the quality control problems of complex medical records, it has also gradually built a blueprint for smart medical records.

Now, thanks to the strong support from policies in the AI ​​medical industry across the country, and the related subdivisions gradually showing a clear profit model, the market has finally ushered in a period of explosive growth. Taking AI medical devices as an example, from a global perspective, the market size of AI medical devices has grown from US$86.5 million in 2016 to US$506 million in 2021, with a compound growth rate of 42.4%, and is expected to grow to US$3.496 billion in 2024. The compound growth rate in the next three years will be 118.5%. AI medicine is showing endless potential.

Where is “AI Medical” headed?

With the explosion of ChatGPT and Baidu’s merger and acquisition, the AI ​​medical market has become a hot topic, and AI medical care is also penetrating into more different medical service scenarios, including AI-assisted diagnosis, AI medical imaging, AI new drug research and development, AI Health management and other fields have gradually become popular subdivisions. However, the problems encountered in their respective fields are also the driving force for AI medical care to continue to move forward.

With the improvement of AI image recognition capabilities, medical imaging has gradually become one of the areas where AI is deeply involved. As the clinical market demand surges, the market potential of AI medical imaging has been highlighted. Tencent, iFlytek, and Infer Technology have all deployed AI medical imaging. However, AI medical imaging companies face problems such as high cost of obtaining high-quality data. The top priority is to break down the barriers between high-quality images in head hospitals and establish a regional sharing mechanism.

AI-assisted diagnosis can effectively support doctors’ clinical diagnosis and treatment decisions. At present, auxiliary medical scenarios extend to medical guidance robots, electronic medical records, virtual assistants, etc. However, the auxiliary medical scenario has very high barriers for information companies, and the knowledge bases of many companies cannot fill the clinical needs of doctors. The solution lies in the openness and real-time updating of the database.

Using algorithmic capabilities to assist in the research and development of new drugs is also one of the important application scenarios. At present, although many artificial intelligence companies have entered the field of new drug research and development, they generally face problems such as long drug research and development cycles, high research and development costs, and low research and development success rates. With the algorithm advantages of artificial intelligence, drug candidate compounds can be virtually screened, thereby gradually reducing the development costs of new drugs.

The application scenarios of AI health management focus on risk identification, virtual nurses, mobile medical care, wearable devices, etc. However, at present, common problems are mainly the public's low awareness of its concept, the lack of corresponding professionalism among those engaged in health management, and the weak correlation of data related to patient smart devices. The top priority is that AI can help health managers build a platform and use a complete knowledge map to provide patients with optimal health management plans.

In addition, medical education, hospital administration, clinical research, etc. are also key areas for exploring and applying artificial intelligence solutions to empower medical staff. Among them, the integration of AI and work management processes can help clinical medical staff be released from daily trivial administrative affairs, allowing them to focus on patient diagnosis and treatment more efficiently. The combined application of medical education and AI takes the reality of the medical system into consideration, allowing clinical medical staff to be more empathetic to patients, and helps clinical medical staff learn professional skills more effectively and adapt more calmly to dynamic changes in the medical environment. .

Joining hands with GBI, Baidu’s layout

The topic returns to Baidu’s acquisition of GBI Health. Coincidentally, Baidu's acquisition of GBI Health occurred after the official announcement of Wen Xinyiyan. We are currently unsure of Wenxinyiyan's participation in GBI Health, but what is certain is that Baidu will definitely inject artificial intelligence capabilities into GBI Health. Help the development of the medical industry. According to industry speculation, GBI Health, which has massive medical and device data, is expected to be combined with Wen Xin Yiyan to become a medical professional think tank with more comprehensive data and smarter interactions. In the future, when GBI Health is deeply integrated with core businesses such as Baidu Health and Lingyi Zhihui and Baidu's core AI technology, Baidu may create an artificial intelligence application model for the medical industry.

In the medical field, what is the existence of GBI Health? According to the data, GBI Health was established in Shanghai in 2002 and is the first medical information data provider in China. It has always been committed to being driven by data and technology to provide pharmaceutical companies, devices and industry-related service providers with holographic information throughout the global pharmaceutical and device life cycle. High-value insights such as data, industry information, and global news help companies lead the market in strategic layout, product decisions, and market insights.

GBI Health currently has three databases including SOURCE global drug database, METRIX researcher database, and DEVINT medical device database, which run through the drug and device development life cycle. It is reported that GBI has been working in the field of medical information intelligence for more than 20 years, and its customer base covers multinational pharmaceutical companies such as Eli Lilly, Sanofi, and Pfizer, innovative pharmaceutical companies such as Innovent Biologics, Fosun Pharma, CStone Pharmaceuticals, and WuXi AppTec, etc. CRO enterprise.

GBI and Baidu have joined forces to bring many possibilities to the industry. On the one hand, GBI will deeply integrate with Baidu HCG's powerful data, technology, and resources to launch a new business intelligence service segment to provide fully closed-loop business decision-making assistance covering the entire medical and health industry. On the other hand, Baidu Medical NLP and big data management technology, which have been carefully polished and applied in the medical field, will improve the entire GBI link from data acquisition, data management to accurate data search and matching efficiency, empowering medical device customers' research and development, clinical trials, and registration. , access, sales, investment and financing transactions and other aspects to comprehensively assist enterprises in their commercial layout.

Written at the end

ChatGPT once again made artificial intelligence popular. IDC data shows that the total value of the artificial intelligence application market is expected to reach US$127 billion in 2025, of which the medical industry will account for nearly 20% of the total application market. AI medical care can essentially rely on its excellent algorithms and big data analysis to continuously penetrate into the data resource layer and technical application layer of relevant service platforms, break through the data barriers of each service port, reduce the overall medical cost, and realize the application of medical imaging and auxiliary services. The perfect implementation of core application scenarios such as diagnosis and treatment, health management, new drug research and development, disease prediction, virtual assistants, process management, and research platforms will ultimately improve the overall domestic medical level.

Baidu’s acquisition of GBI Health, a medical business solution service provider, once again reflects that “AI medical care” is the key to the development of the medical industry. With the rapid development of China's pharmaceutical industry, massive medical information data continues to accumulate, and the database of scientific research progress will bring huge commercial value to life and health companies and promote the vigorous development of the AI ​​medical industry. To develop the AI ​​medical industry, it depends on the strength of major companies.

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