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Using AI to Put the Patient First

AI Health uses the power of Artificial Intelligence to help address the existing pain points in healthcare around data management, remote patient monitoring, and chronic disease treatment.

Unifying the Healthcare Data Ecosystem

Solving Healthcare Pain Points with AI + IoT

From industry level down to patient level.

Disconnected Systems

Under-utilized Assets

Accessibility to Care

Access to Telehealth

Biased Study Structure

Multiple icons representing five different challenges the medical industry faces today. The first one is disconnected systems. It shows an electronic cable with one end sliced open and exposing three smaller wires. The second icon is Under-utilized Assets. It shows a cube with programming code on its’ sides. The third icon is Accessibility to Care. It shows a broken heart with one side containing a healthcare cross and the other side containing a dollar sign. The fourth one is Access to Telehealth. It shows a laptop with a lock symbol on the screen. The last icon is Biased Study Structure. It shows a book with an unbalanced justice scale on the front.

Addressing Algorithmic

Bias in Healthcare

Creating an ethical approach to AI to truly be patient-centric for all.

Infographic representing Addressing Algorithmic Bias in Healthcare. It contains three parts. The center contains the scales of justice. On the left, is a group of doctors. All of which are different ethnicities and genders. On the right, is a group of patients. All of which are different ethnicities, genders and ages.
A two part infographic connected by an artificial intelligence pipeline. The first infographic features the AI Health logo inside a computer chip. It is surrounded by four other icons in a circle. The first icon is a pie chart. The second icon is a heart with a checkmark inside it. The third icon is a light bulb. The last icon is a bar graph. The next infographic contains a multicultural group of people. They are different ages, races and genders. They are all standing together. One is in a wheelchair and working on a laptop. There is also a boy and a girl in this group.

Advancing Equitable

Personalized Health with AI

Committed to advancing equitable personalized care around chronic illness through a series of groundbreaking validation studies.

Reinventing Remote Care

Increasing access to telehealth through a cost efficient remote patient monitoring system powered by AI.

Addressing the

Problems that Matter Most

Focused on unlocking the promise of AI in healthcare to provide more personalized care for patients around chronic illness.

Infographic to represent Addressing the Problems that Matter Most. Features a AI Health logo inside a circle. It is surrounded by six medical industry icons. Icons include, laptop with health insurance data, wearable medical wristband device, blood glucose readers, mobile phone with medical data, medical analytics bar graph, and a laptop with medical data. To the right of this graphic features a woman doctor with olive skin and black hair. She is next to four icons. The icons are displayed as a pie chart, lightbulb, bar graph and heart with a checkmark inside it.

Addressing Algorithmic Bias in Healthcare

Creating an ethical approach to AI to truly be patient-centric for all.

Infographic representing Addressing Algorithmic Bias in Healthcare. It contains three parts. The center contains the scales of justice. On the left, is a group of doctors. All of which are different ethnicities and genders. On the right, is a group of patients. All of which are different ethnicities, genders and ages.
Icon representing Biased Study Structure. It shows a book with an unbalanced justice scale on the front.

Biased Study Structure

Historically biased study structure to focus on better results for study, not most inclusive for under-represented patients.

Icon representing Under-utilized Assets. It shows a cube with programming code on its’ sides.

Under-utilized Assets

Millions of data records containing critical information are disaggregated and overlooked.

Icon representing Access to Telehealth. It shows a laptop with a lock symbol on the screen.

Access to Telehealth

Lack of universal connectivity to be able to engage with the system, and ability to afford remote care.

Icon representing Accessibility to Care. It shows a broken heart with one side containing a healthcare cross and the other side containing a dollar sign.

Accessibility to Care

A data divide exists between those that use primary care vs those that use the ER for care.

Icon representing disconnected systems. It shows an electronic cable with one end sliced open and exposing three smaller wires.

Disconnected Systems

Lack of continuity in patient data especially for  underserved communities.

Solving Healthcare Pain Points with AI + IoT

From industry level down to patient level.

In order to benefit underserved and marginalized communities, artificial intelligence design and applications must be intentional. This requires understanding the complex systems involved and how bias is already embedded within them. Otherwise, we risk replicating and potentially worsening the existing systemic and institutional barriers. AI Health hopes to use ethical and deliberate AI practices to improve health outcomes for all patients.

Portrait of Juan C. Espinoza, MD, FAAP. He is of latin ethnicity. Smiling and wearing a brown coat, maroon vest, striped collard shirt and two earrings. Full groomed beard and mustache.

Juan C. Espinoza, MD, FAAP

AI Health Chief Medical Officer and Chairman of the AI Health Clinical and Technical Oversight Board

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Wireless technology, digital databases, and computerized algorithms together will power advances in precision health and AI Health is poised to deliver novel important solutions by applying these technologies.

David C. Klonoff, MD, FACP, FRCP (Edin), Fellow AIMBE 

AI Health Advisor and Member of the AI Health Clinical and Technical Oversight Board

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Integrating available digital and diabetes technologies with patients’ unique characteristics and biomedical data has the potential for improving personalizing care, facilitating decision-making, and increasing access to optimal care. AI Health has the potential for accelerating this vision to enable better care delivery with the goal of improving clinical and patient-reported outcomes.

Portrait of Francisco J. Pasquel, MD, MPH. He is a middle aged male with black hair. He is smiling and clean shaven. He is wearing a black coat and blue collard shirt.

Francisco J. Pasquel, MD, MPH

AI Health Advisor and Member of the AI Health Clinical and Technical Oversight Board

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With diabetes technology becoming more available in Guam, including continuous glucose monitoring systems and insulin pumps, patients are seeing improvement in their diabetes management. Using AI techniques will give us more tools to improve outcomes.

Portrait of Erika M. Alford, MD. She is a middle aged Asian Pacific Islander woman with shoulder length hair She is smiling and her hair is brown. She is wearing a rose pink dress and a gold necklace.

Erika M. Alford, MD

AI Health Advisor and Member of the AI Health Clinical and Technical Oversight Board, and Principal Investigator for Diabetes Study Guam

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David C. Klonoff, MD, FACP, FRCP (Edin), Fellow AIMBE

AI Health Advisor and Member of the AI Health Clinical and Technical Oversight Board
Wireless technology, digital databases, and computerized algorithms together will power advances in precision health and AI Health is poised to deliver novel important solutions by applying these technologies.
Portrait of Francisco J. Pasquel, MD, MPH. He is a middle aged male with black hair. He is smiling and clean shaven. He is wearing a black coat and blue collard shirt.

Francisco J. Pasquel, MD, MPH

AI Health Advisor and Member of the AI Health Clinical and Technical Oversight Board
Integrating available digital and diabetes technologies with patients' unique characteristics and biomedical data has the potential for improving personalizing care, facilitating decision-making, and increasing access to optimal care. AI Health has the potential for accelerating this vision to enable better care delivery with the goal of improving clinical and patient-reported outcomes.

Juan C. Espinoza, MD, FAAP

AI Health Chief Medical Officer and Chairman of the AI Health Clinical and Technical Oversight Board
In order to benefit underserved and marginalized communities, artificial intelligence design and applications must be intentional. This requires understanding the complex systems involved and how bias is already embedded within them. Otherwise, we risk replicating and potentially worsening the existing systemic and institutional barriers. AI Health hopes to use ethical and deliberate AI practices to improve health outcomes for all patients.
Portrait of Erika M. Alford, MD. She is a middle aged Asian Pacific Islander woman with shoulder length hair She is smiling and her hair is brown. She is wearing a rose pink dress and a gold necklace.

Erika M. Alford, MD

AI Health Advisor and Member of the AI Health Clinical and Technical Oversight Board, and Principal Investigator for Diabetes Study Guam
With diabetes technology becoming more available in Guam, including continuous glucose monitoring systems and insulin pumps, patients are seeing improvement in their diabetes management. Using AI techniques will give us more tools to improve outcomes.

Making Diabetes HISTORY on GUAM

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