Mobile health (mHealth) programs utilize automated voice messages to deliver health information, particularly targeting underserved communities, demonstrating the effectiveness of using mobile technology to disseminate crucial health information to these populations, improving health outcomes through increased awareness and behavioral change. India's Kilkari program delivers vital maternal health information via weekly voice calls to millions of mothers. However, the current random call scheduling often results in missed calls and reduced message delivery. This study presents a field trial of a collaborative bandit algorithm designed to optimize call timing by learning individual mothers' preferred call times. We deployed the algorithm with around $6500$ Kilkari participants as a pilot study, comparing its performance to the baseline random calling approach. Our results demonstrate a statistically significant improvement in call pick-up rates with the bandit algorithm, indicating its potential to enhance message delivery and impact millions of mothers across India. This research highlights the efficacy of personalized scheduling in mobile health interventions and underscores the potential of machine learning to improve maternal health outreach at scale.

Automated voice calls with health information are a proven method for disseminating maternal and child health information among beneficiaries and are deployed in several programs around the world. However, these programs often suffer from beneficiary dropoffs and poor engagement. In previous work, through real-world trials, we showed that an AI model, specifically a restless bandit model, could identify beneficiaries who would benefit most from live service call interventions, preventing dropoffs and boosting engagement. However, one key question has remained open so far: does such improved listenership via AI-targeted interventions translate into beneficiaries' improved knowledge and health behaviors? We present a first study that shows not only listenership improvements due to AI interventions, but also simultaneously links these improvements to health behavior changes. Specifically, we demonstrate that AI-scheduled interventions, which enhance listenership, lead to statistically significant improvements in beneficiaries' health behaviors such as taking iron or calcium supplements in the postnatal period, as well as understanding of critical health topics during pregnancy and infancy. This underscores the potential of AI to drive meaningful improvements in maternal and child health.

For public health programs with limited resources, the ability to Public health programs play an essential role in improving the predict how behaviors change over time and in response to interventions health outcomes of individuals and communities, often through education is crucial for deciding when and to whom interventions and subsequent behavioral change. Some health programs should be allocated. Using data from a real-world maternal interact with their intended beneficiaries in a broad and infrequent health program, we demonstrate how a cognitive model based on manner. For example, a campaign about the health risks of smoking Instance-Based Learning (IBL) Theory can augment existing purely may address a general population of smokers through scattered computational approaches. Our findings show that, compared to advertisements in the media [18]. Others rely on repeated direct interactions general time-series forecasters (e.g., LSTMs), IBL models, which with their intended beneficiaries. For example, maternal reflect human decision-making processes, better predict how individuals' health programs that send automated messages about exercise and behaviors change over time (transition-consistency) and nutrition to enrolled expectant mothers [13]. In this case, it is crucial in response to receiving an intervention (intervention-sensitivity).

There is no doubt that AI in healthcare has achieved unbelievable progress. AI technology in healthcare industry has modernized the conventional approaches in the upcoming years. AI technology is slowly converting the medical field with robustness. Due to this, the app development company has advanced AI-based services and solutions that convert the medical field and healthcare into this digital world. AI, along with drug development and automating admin tasks, technology is so helpful in screening public health programs.

Since last January, when we launched our AI for Health program, we've been dedicated to using AI and data science to help improve the health of people and communities worldwide. As we reflect on how the world has changed this past year due to the pandemic, we want to take a moment to shed light on the great work our grantee partners are doing to tackle some of the most difficult health challenges. Our AI for Health program's commitment is to empower grantees. To date, we have awarded over 180 grants in four areas of focus, which include accelerating medical research, increasing global health insights, addressing health equity and building research capabilities. Access to Microsoft's technology such as Azure High Performance Computing, Azure Machine Learning, Power BI, Return to School Power Platform solution and the SmartNoise differential privacy platform have accelerated the progress made in grantee research.

Undoubtedly, Artificial Intelligence (AI) in medicine has and will have unbelievable potential. The AI technology in medicine will modernize conventional approaches in the next couple of years. AI technology is slowly transforming the medical field with robustness. That's why USM is ready with advanced AI-based solutions and services to transform healthcare and medical fields into this digital world. Manual management of such programs is a complex process.

IMAGE: Covax-19 is an Australian-developed COVID-19 vaccine developed with the help of computational and artificial intelligence (AI)-based technologies. Given the global urgency of the COVID-19 pandemic, Microsoft's AI for Health program has stepped in to support the development and potential deployment of Vaxine's COVAX-19 vaccine with a philanthropic grant. Vaxine Pty Ltd, a biotechnology company based in South Australia, uses computational and artificial intelligence (AI)-based technologies to accelerate pandemic vaccine and drug development with the aim to reduce drug development processes that normally take decades down to just weeks. The Microsoft AI and Azure cloud capabilities will help the company accelerate clinical testing of its COVAX-19 vaccine. "Large international Phase 3 vaccine trials are extraordinarily complex and generate vast amounts of data that needs to be efficiently processed", says Vaxine Research Director, Flinders University Professor Nikolai Petrovsky.

The Mount Sinai Health System has received an award from Microsoft AI for Health to support the work of a new data science center dedicated to COVID-19 research. The Mount Sinai COVID Informatics Center (MSCIC) brings together leaders from entities across Mount Sinai, including the Hasso Plattner Institute for Digital Health, the Department of Genetics and Genomic Sciences, and the BioMedical Engineering and Imaging Institute. "This partnership with Microsoft provides us with cloud resources that will accelerate our discovery, translation and implementation of digital tools in the fight against COVID-19," said Robbie Freeman, MSN, RN, vice president of Clinical Innovation at The Mount Sinai Hospital. "Through this collaboration with AI for Health, we are leveraging the expertise of the Mount Sinai Health System in delivering world-class patient care and the Azure cloud to bring our AI-enabled products from bench to bedside." The philanthropic Microsoft AI for Health Grant will support the care of patients with the coronavirus, enabling the Center to develop tools using artificial intelligence (AI) that enhance care and evidence-based medicine for treating COVID-19 patients.

Microsoft plans to spend $40 million to support collaborative projects leveraging artificial intelligence for medical research and discoveries. The five-year program, called AI for Health, is the fifth program Microsoft has rolled out as part of its AI for Good initiative, the tech giant announced Wednesday. Microsoft's AI for Good is a $165 million program to provide researchers and nonprofits with technology tools to address pressing concerns such as global climate, humanitarian and accessibility issues. "Artificial intelligence has the potential to solve some of humanity's greatest challenges, like improving the health of communities around the world," said Brad Smith, president of Microsoft, said in a statement. Microsoft CEO Satya Nadella said in a statement that AI "represents one of technology's most important priorities, and healthcare is perhaps AI's most urgent application."