HAIS - Healthcare AI Systems

We are addressing the significant global challenge of healthcare accessibility and diagnostic accuracy, particularly in underdeveloped regions. Globally, over one billion people lack access to healthcare facilities due to geographic and economic barriers. The WHO reports that in low-resource settings, the ratio of healthcare workers to the population severely falls below the minimum threshold, leaving many without basic medical care. Diagnostic inaccuracies further complicate the issue, with error rates in some regions reaching as high as 45%, compared to 5-15% in developed countries.

The number of people worldwide who cannot receive healthcare is quite high, according to United Nations reports. In 2021, 828 million people could not access healthcare due to factors such as hunger and malnutrition. This number has increased by approximately 46 million people since 2020, and due to the COVID-19 pandemic, this number has increased by 150 million people. Hunger, food insecurity and malnutrition show that the United Nations is moving further away from its goal of ending these problems by 2030.

Our solution specifically targets these problems by harnessing artificial intelligence to provide reliable and accessible mobile and home-based diagnosis. This approach is crucial in areas where the scarcity of medical professionals and facilities exacerbates health disparities. By enabling individuals in remote or underserved regions to perform preliminary diagnostics at home, we significantly reduce the dependency on physical healthcare infrastructures and improve early detection and treatment of diseases, which is often critical for successful outcomes.

Our solution will primarily serve individuals in underdeveloped and remote areas who are currently underserved in terms of healthcare access and diagnostic services. These populations often face barriers such as long travel distances to healthcare facilities, high costs of medical services, and a shortage of qualified healthcare professionals. As a result, many health conditions go undiagnosed or are detected too late, which can lead to preventable complications and higher mortality rates.The impact of our AI-driven home diagnosis tool is multifaceted:

Accessibility: Our solution provides an app and tool to perform basic health diagnostics at home, greatly reducing the need for travel to remote healthcare facilities. This is particularly beneficial for those in rural or isolated communities.

Early Detection: Our app enables earlier detection of health conditions which can be critical for effective treatment and improved health outcomes. Early detection is particularly significant for diseases such as diabetes, heart conditions, and infectious diseases, where early intervention can lead to better management and prognosis.

Cost-Effective: Reducing the frequency of visits to healthcare facilities for routine checks or initial diagnostics can significantly lower healthcare costs for individuals and/or goverments and families in economically disadvantaged regions.

Education and Empowerment: By integrating educational components into our tool, we also empower individuals to take charge of their health. This includes information on when and how to seek further medical advice, thus fostering a better understanding of their health conditions.

Overall, our solution addresses the critical needs of a population that is currently under-equipped with the necessary tools to manage their health effectively. By improving access to healthcare services, we aim to enhance the overall quality of life and reduce the healthcare disparities faced by these communities.

Together with our team, we completed 5 separate artificial intelligence studies in 8 weeks. All friends in the team are volunteers who are enthusiastic about making artificial intelligence more usable. Thanks to our motivation, we completed some of the side work on the way to our main work in a period of 2 months and we continue to complete it.

We have made very rapid progress so far in the diagnosis of diseases with our expert veterinarian friend, who plays the most important role in the study we will start in cats because it is easier to obtain data, and we continue our work at the same pace.

As people living in Turkey, the number of people lost in our country due to incorrect or late diagnosis is very high. As the team leader, I lost my mother due to a cancer that was diagnosed late. A cancer that could have been diagnosed approximately 8 months ago could only be diagnosed when it reached the 3rd stage. During this period, 3 different doctors could not detect any cancer with clear symptoms. The fact that the number of necessary qualified doctors in our country is very low, and the ones available are in 2-3 big cities, makes a large part of Turkey a pilot region. All his teammates are people who know that the way to love people is to love animals. One of our most important sources of motivation is that we will start from animal health first, as data collection is easier in animals. That's why we want to be able to offer the work we do for both animal health and human health under suitable conditions to the regions that really need it. In this respect, we can establish the necessary empathy to help NGOs, organizations, municipalities and states working in critical regions, because we experience the same difficulties in different ways from time to time. We also look forward to working with regions that need much more basic healthcare.

With artificial intelligence, we currently have artificial intelligence systems that provide accurate results on the diagnosis of pneumonia, heart attack risk, tuberculosis disease diagnosis, brain tumor diagnosis for cats and humans, FIP disease diagnosis in cats. The AI part of the project is in prototype form but the device part is currently in the concept stage.

We attend to meet people who will contribute to our work, expand our network, and to introduce our work and AiMinds to the world.

In addition, by joining MIT Solve, we want to reach out to organizations and NGOs working in regions where access to healthcare is difficult, present our system to them, and further develop our system with the data we receive from them. We are sure that we will meet many stakeholders with whom we can help and provide added value.

Our HAIS solution offers an innovative approach to expand access to healthcare services and enhance diagnostic accuracy.

Equal Access to Healthcare: Providing equal access to healthcare services for everyone, especially those in remote and underserved regions, represents a significant step forward.

Detailed Health Records: By capturing individuals' health histories more accurately and in detail, it will enable better health management over time.

Early Diagnosis and Prevention: The advanced AI technology used in our solution enables early diagnosis of diseases, allowing for timely preventative measures.

Minimizing Human Error: This solution will reduce human error in diagnostics in both developed and developing countries, enhancing the reliability of diagnostic processes.

Portable and Cost-Effective Devices: Our AI-supported test systems will reduce costs with smaller, portable devices, making it feasible for every household to use them.

Health Tests from Home: It will enable elderly, bedridden, and disadvantaged groups to conduct tests at home and have results sent directly to their doctors.

Animal Health: Starting with the treatment of animals, our work will not only help sick animals but also prevent diseases in healthy ones by taking preemptive health measures.

AI-Powered Analysis: As the system evolves, it will provide enhanced capabilities for resolving critical health situations based on the data requested by AI.

This innovative solution aims to make health systems more equitable, accessible, and efficient, creating broad impacts across the healthcare landscape.

In underserved and remote areas, many individuals lack access to healthcare facilities, leading to delayed diagnosis and treatment of diseases, which exacerbates health disparities and outcomes.

How:
AI technology is used to develop diagnostic tools that are easy for the general public to use, enabling early detection of health conditions from home. These devices are distributed to people in underserved and remote areas where access to healthcare facilities is typically limited. Users receive training and ongoing support to ensure they can effectively use these devices, maximizing their potential benefits.

Why:
With earlier and more accessible diagnosis, individuals can seek treatment sooner, potentially before conditions worsen. As these tools reach more people, everyone has a better chance of receiving timely and effective medical interventions, thus improving overall health equity. Continuous data collection and analysis refine the AI algorithms within these devices over time, leading to better outcomes and providing a scalable, impactful solution that addresses the core issues of healthcare accessibility.

We will use specific indicators to monitor and evaluate this process: the number of devices distributed and actively used in target communities, the frequency of device usage by individuals, health outcomes data before and after device implementation, and user satisfaction and feedback collected through surveys and interviews. By methodically planning and documenting each step of our theory of change, we will ensure that HAIS not only addresses immediate health needs but also contributes to systemic changes in healthcare access and equity. This structured approach will align our project's goals with evidence-based strategies, ultimately increasing the likelihood of achieving significant and sustained impacts.

First of all, we will launch HAIS as a pilot study in the earthquake zone in Turkey. Even though a year has passed since the earthquake, not even a detailed health screening of the earthquake victims was carried out. Psychological problems in the region aside, we will provide one of the most important needs of earthquake victims who feel the difficult living conditions to the region, free of charge. There is currently no precise information about how many people live in the earthquake area and what kind of health problems they have. With a general study we will carry out in the region, we will meet the needs of the region regarding disease diagnosis and treatment under the health service. We will also make the system available to refugees who live in the earthquake zone and cannot benefit from state health services. Thanks to HAIS, we plan to minimize the health problems of earthquake victims in the region, who receive regular health checks, and solve the health problems of earthquake victims in diseases that require serious intervention, both with our own organization and with NGOs working in the region.

In addition, we will ensure that the system operates more effectively and more successfully through continuous improvements. In this respect, regions with higher disease propensity offer much more valuable working opportunities for us. The clinics and hospitals that we will determine as pilot study areas also play an important role in taking our work forward.

If requested, we can share our system under appropriate conditions with both NGOs working in the region and organizations doing similar work in other countries.

Our solution, HAIS - Healthcare AI Systems, utilizes a combination of cutting-edge artificial intelligence (AI) technology and advanced sensor-based hardware to provide accessible and accurate health diagnostics directly from the comfort of one’s home. Here is a detailed breakdown of the core technology that powers HAIS:

     Artificial Intelligence and Machine Learning:

• Diagnostic Algorithms: At the heart of HAIS is a suite of AI algorithms designed to analyze health data from non-invasive sensors. These algorithms leverage machine learning to improve over time, learning from each interaction to enhance diagnostic accuracy.
• Predictive Analytics: Our AI uses historical data and predictive models to identify potential health risks before they become critical, enabling preventive care measures.

     Sensor Technology:

• Biometric Sensors: These are integrated into easy-to-use devices that can capture vital health metrics such as heart rate, blood pressure, temperature, and more. The sensors are designed to be non-invasive and user-friendly, making them suitable for a wide range of users, including elderly and bedridden patients.
• Data Accuracy: Enhanced sensor technology ensures that the data captured is of the highest fidelity, which is critical for reliable diagnostics.

     Mobile and Web Applications:

• User Interface: Users interact with the HAIS system through a mobile or web application, which displays health data in an easy-to-understand format. The app also provides actionable insights and recommendations based on the AI’s analysis.
• Data Integration: The app integrates seamlessly with the hardware to collect and transmit data securely to the cloud for processing by our AI algorithms.

     Cloud Computing:

• Data Storage and Analysis: All health data collected by our devices are securely stored and analyzed in the cloud, ensuring scalability and the ability to handle large volumes of data without compromising performance.
• Privacy and Security: We employ advanced encryption and data privacy measures to protect sensitive health information, adhering to the highest standards of healthcare compliance.

     Telehealth Integration:

• Remote Monitoring: Health professionals can monitor patients’ health data remotely, enabling timely interventions even from a distance.
• Communication Tools: Integration with telehealth platforms allows for seamless communication between patients and healthcare providers, facilitating better care coordination and management.

Educational Content and Support:

• Health Education: The app provides users with educational content about common health conditions and how to manage them, empowering users with knowledge to take proactive steps in managing their health.
• Technical Support: Comprehensive support ensures that users can effectively utilize the technology, regardless of their tech proficiency.

By combining AI with advanced sensor technology and mobile connectivity, HAIS not only addresses the challenge of healthcare accessibility but also ensures that each user can have personalized and accurate health monitoring. This holistic approach not only meets the needs of our target communities but also aligns with global health objectives, driving forward the mission of enhancing healthcare through technological innovation.

We are full of 14 volunteers as 6 AI engineers, 1 full-stack engineer, 1 cloud engineer, 1 planning engineer, 1 veterinarian, 1 SEO supervisor, 1 reporting supervisor, 1 CBO and 1 CEO.

We are working for 3 months.

There are 9 females and 5 males in our team. Although they all come from different cultures and ideologies, one of the things we attach most importance to as a working principle is to respect these values.

We design our working system as a system that has never been created before and we emphasize the element of mutual respect. Individuals see their teammates as real friends and work in a way that they can take on each other's work and support each other in the momentary or seasonal events that life throws at us. In this sense, we take an approach that trusts each other and does not doubt each other's good intentions.

One of the most important points is that we are a team that creates free time for itself when necessary, can do additional work for projects, and can play games such as UNO to improve team spirit and competition when necessary.

When we set up the organization and started working in real terms, there is a very important rule that we adopted from the beginning; Everyone will receive equal wages. People will come to positions such as managers and executives not because they will receive higher salaries, but because they will be able to take responsibility. It destroys the status-based hierarchical structure and establishes a brand new structure based on respect, which is one of the most important rules internalized by the entire team. When people delay a task, they become embarrassed out of respect. In our opinion, the path to success is team responsibility that develops together with self-responsibility.

In the AiMinds team, everyone can criticize each other at the right points and everyone is open to criticism. In case of any mistake, everyone takes responsibility, especially the team leader. We can say that we have a complete team spirit with these approaches.

Our business model is centered around delivering high-quality, accessible health diagnostics powered by artificial intelligence directly to consumers, especially targeting underserved regions. We will provide devices that can perform blood and urine analysis, leveraging AI to ensure high diagnostic accuracy. These devices are portable and designed for use at home, which is critical for our target populations who have limited access to traditional healthcare facilities.

Customers will choose our products because they provide a convenient, reliable and affordable option for health monitoring and early diagnosis, significantly improving health outcomes. Our revenue comes from the sales of these diagnostic devices and a subscription model for ongoing updates and AI analytics services, ensuring that the technology remains at the cutting edge and maximizes utility for users.

This dual revenue stream will ensure we can sustain our operations while scaling our impact. The recurring revenue from subscriptions helps fund continual improvements and expansions into new markets. Proof of the success of our business model is seen in the market calculations we will create for animal health.

There are approximately 110 million domestic cats in the world. When we include domestic animals such as dogs and birds, the total number is approximately 300 million. When we include the number of animals raised on farms, the number reaches billions. This will be the market where we will primarily make profits.

The artificial intelligence model we will create to track the parts of FIP positive diets we will apply will be able to produce technologies not only for animal health but also for human health. We will create a market with the free application, which we plan to experience only in the third part of the year at the latest, if animal health deteriorates. The first version we will offer for free will be an artificial intelligence application that can determine probabilities based on blood values. As for the last records of the year, we will launch an uninterpretable version of records such as MRI and X-ray, which can provide more advanced reports, with two separate membership models for animal owners and veterinarians. In the next stage, our artificial intelligence is trained to predict possible diseases and launch the current system. With 10% of the world's population having pets and only 10% of them using our service, we will create a market worth approximately 250 to 400 million dollars. We expect a 500% increase in just 6 months of using the service, earning at least more than $1.250 billion. With an annual revenue of more than $15 billion, pet health insurance will be worth $246 billion in 2023. Just one application provides 6% growth. We will create more than 15% growth with the membership model we will create for veterinarians and animal product manufacturers. 

Apart from this application, the artificial intelligence we will run on the intensive care service will increase this growth much higher. In addition, imaging-related products are planned to replace large devices in clinics and even produce products produced in every home with artificial intelligence innovation. Only with the application, the biggest payment in the pet market will belong to us in 2025.

While the human health study that will run in parallel with this study will provide more effective diagnosis and treatment in developed countries, users using our system will also help people in underdeveloped countries. While we will use some of our income to help organizations working in underdeveloped countries, we will also use some of it to carry out our own work.

HAIS will be a system that all companies producing wearable technological products will have to work in an integrated manner, which can process all health data and track the health status of people.

This will be the point where we will break the inequality between underdeveloped and developed countries. While we will use some of our earnings for our expenses and new projects, we will also use some of it to ensure that all living things in underdeveloped countries can receive health care under more equal conditions. We will continue the technological development of hospitals in underdeveloped countries with the shares we will allocate from our budget. Perhaps we will have opened an important window for the United Nations to achieve its 2030 goals.