Google wants to make it easier to develop health apps, and to that end, it introduced during The Check Up, the company's annual health event, Open Health Stack,, an open source kit built on an interoperable data standard. The Open Health Stack aims to accelerate the creation of applications for healthcare professionals who need access to information and insights to make informed decisions. For example, nurses can have the information they need to care for patients in rural areas or query population data to monitor the health of a community. One of the components of Open Health Stack is the Android FHIR SDK, which ensures security and privacy of the data stored in the app, and also make it accessible offline so it can be used even in locations without cellular coverage or Internet access. Open Health Stack also provides design guidelines to improve the experience for healthcare professionals. Google is sharing partner stories to show how the Open Health Stack is being applied in different use cases. One such case is in Kenya, where a maternal health app supports volunteers to work with pregnant women in rural communities. More news at The Check Up Also during the event, Google highlighted that it has spent the last few years researching Artificial Intelligence (AI) targeting healthcare. Advances from the company have to do with Large Language Model (LLM - Artificial Intelligence (AI) tools used in understanding and generating dialogues in text) and partnerships that are bringing solutions to the real world and new ways to detect diseases. In the LLM field, Google introduced in 2022 the Med-PaLM app, a version of PaLM adjusted for the medical field and, according to Google, the first to obtain a "pass score" higher than 60% on medical licensing questions in the United States, even presenting justifications. Recently, Med-PaLM 2 showed consistent performance for "expert" level medical examination questions, with a score of 85%. In the area of partnerships, Google unveiled a partnership with Jacaranda Health, a Kenyan-based nonprofit focused on improving health outcomes for mothers and babies in government hospitals through digital solutions. In sub-Saharan Africa, maternal mortality is high and there is a shortage of professionals trained to operate ultrasound machines widely used to assess pregnancy progress. Through this partnership, exploratory research will be conducted to apply AI tools to support on-site ultrasound examinations of pregnant women. Another partnership was made with the Chang Gung Memorial Hospital (CGMH) in Taiwan also around the use of ultrasound, but this time for breast cancer detection. In addition to mammography, which may be less effective for certain populations, such as those with higher breast density, ultrasound scans are always recommended to detect early evidence of cancer. The partnership also explores AI models in this endeavour using ultrasound. The third initiative relates to work done with the Mayo Clinic three years ago. In this case, AI is supporting the time-consuming process of planning radiotherapy. One intensive step in that process is a technique called "contouring", in which doctors draw lines on CT scans to separate cancer areas from nearby healthy tissue that could be damaged by radiation. This process can take up to seven hours for a single patient. The results of the study and the radiotherapy model developed will be published soon. Further research will be conducted under this partnership. Google is also working with partners to study in care settings the results of research on screening chest x-rays of suspected tuberculosis using AI. According to the WHO, tuberculosis is the ninth leading cause of death in the world, with over 25% of tuberculosis deaths occurring in Africa. Although it is treatable, tuberculosis requires cost-effective screening solutions for early detection of the disease and reducing the spread in communities. A partnership with an organisation led by Right to Care, a non-profit with extensive experience in treating tuberculosis in Africa, will make testing using AI widely available across sub-Saharan Africa. Google and exam images Google wants healthcare organizations to use its software and servers to read, store and label X-rays, MRI results and other medical images. With features of the Medical Imaging Suite, announced in October 2022, healthcare professionals will also be able to access health images in a more accessible, interoperable and useful way, including being able to annotate images and create machine learning models for research. "Google pioneered the use of AI and computer vision with Google Photos, Google Image Search and Google Lens. Now we are unleashing our knowledge, tools and imaging technologies to healthcare and life science companies," says Alissa Hsu Lynch, Google Cloud's global leader for healthcare technology strategies and solutions. "Google pioneered the use of AI and computer vision with Google Photos, Google Image Search and Google Lens. Now we are unleashing our knowledge, tools and imaging technologies to healthcare and life science companies," says Alissa Hsu Lynch, Google Cloud's global leader for healthcare technology strategies and solutions. "With technological advances, the size and complexity of medical images have grown. We know that AI can enable faster and more accurate diagnoses and thus help improve the productivity of healthcare professionals," Lynch says in an interview with Forbes. Duel with AWS Google Cloud and AWS are in a race to gain leadership in the medical imaging industry with cloud solutions. Imaging, which encompasses exams such as X-rays, MRIs, ultrasound, CT scans, and endoscopy, is an important diagnostic tool that both facilitates diagnosis and enables you to track treatment outcomes. While Google announced its Medical Imaging Suite to make healthcare images more organised, accessible and interoperable in the cloud, AWS has its Amazon HealthLake Imaging, which stores large volumes of medical images, and Amazon HealthLake Analytics, focused on data analytics, both as features of Amazon HealthLake, a healthcare data cloud platform launching in late 2020. The impression so far is that Google Cloud's focus is on specifics and also on reducing the workload of healthcare professionals, while AWS seems to be taking a more comprehensive approach, looking at medical image retrieval and analytics as a driver of cloud service adoption.