PREDICT

AI-driven risk assessment for early disease detection,
proactive care, and improved health outcomes

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PREDICT

Understanding PREDICT

PREDICT, a deep learning AI model, leverages extensive healthcare data hubs to analyze population health risks and forecast the onset of chronic diseases. Our powerful AI-driven solution processes real-time and historical healthcare data, offering proactive insights into the health status of both individuals and entire populations. PREDICT identifies individuals at risk of conditions such as diabetes, hypertension, ischemic heart disease, chronic respiratory disease and more, equipping healthcare systems with the tools to intervene early, optimize care management, and prevent disease progression.

PREDICT identifies individuals at risk of chronic conditions, equipping healthcare systems with the tools to intervene early and optimize care management.

Diabetes

Cardiovascular Disease

Chronic Respiratory Disease

By leveraging advanced deep learning algorithms, Predict goes beyond simple risk detection. It evaluates real-world healthcare data, including electronic health records (EHRs), claims data, and health information exchanges (HIEs), to provide precise, actionable insights for payers, providers, and regulators. This AI model is already deployed across national healthcare databases, analyzing over 32 million patient records in the UAE and Saudi Arabia, informing key stakeholders about emerging health risks and future complications.

Key Components of PREDICT

By leveraging deep learning AI to transform healthcare decision-making through early disease detection, prognosis modelling, and financial forecasting. Our system analyses vast datasets—including biomarkers, patient history, and lifestyle factors—to detect the earliest signs of disease, often before clinical symptoms appear. This enables timely preventive interventions, targeted screenings, and personalised health strategies that reduce the likelihood of disease progression.

Beyond detection, PREDICT builds prognostic models to assess how a condition could evolve over time at both an individual and population level. By continuously analysing real-time health data, the system improves its risk assessments, determining the probability of disease occurrence and forecasting complications. This empowers healthcare providers with data-driven insights to anticipate risks, tailor treatment plans, and optimise clinical interventions—improving both short- and long-term health outcomes.

In parallel, PREDICT simulates the financial impact of disease, providing healthcare systems with critical foresight into cost implications at both a micro and macro scale. By integrating medical history, treatment costs, and resource utilisation trends, the AI delivers financial alerts, helping stakeholders implement cost-effective interventions. This capability supports proactive budgeting, reduces unnecessary hospitalisations, and enhances resource allocation, ensuring a more sustainable healthcare system while improving patient care.

Early Disease
Detection

Identify Risks
Intervene Early

Our AI models identify risks for chronic conditions, including diabetes, cardio, and respiratory disease, facilitating early interventions and precision care.

Disease Prognosis Modelling

Anticipate Risks
Reduce Complications

Predict anticipates potential disease complication progression over time, enabling early intervention to reduce health deterioration and improve patient quality of life.

Financial Impact Simulation

Cost Forecasting
Resource Allocation

AI-driven cost forecasting optimizes resource allocation, ensuring payers and providers manage financial risks effectively.

See problems before they happen

For Providers

AI-driven real-time insights into patient health trends enhance engagement by providing a transparent view of care progress. Automated IoT and EHR integration reduce manual data collection, while tracking key health indicators helps care teams improve treatment adherence.

For Payers

AI-driven interventions help reduce unnecessary hospitalizations while optimizing resource allocation by identifying high-risk patients in need of urgent care. Additionally, detailed digital health records enhance claims management by streamlining verification processes.

For Regulators

By identifying disease trends at the population level, healthcare systems can support public health initiatives and enable data-driven policy planning. Real-time insights into healthcare risks ensure that national healthcare systems take a proactive rather than reactive approach to managing chronic diseases.

PREDICT

AI-driven risk assessment for early disease detection,
proactive care, and improved health outcomes

Diabetes

Cardiovascular Disease

Chronic Respiratory Disease

Early Disease
Detection

Identify Risks
Intervene Early

Disease Prognosis Modelling

Anticipate Risks
Reduce Complications

Financial Impact Simulation

Cost Forecasting
Resource Allocation

See problems before they happen

For Providers

For Payers

For Regulators

USEFUL LINKS

CONTACT

PREDICT

AI-driven risk assessment for early disease detection, proactive care, and improved health outcomes

Diabetes

Cardiovascular Disease

Chronic Respiratory Disease

Early DiseaseDetection

Identify Risks Intervene Early

Disease Prognosis Modelling

Anticipate Risks Reduce Complications

Financial Impact Simulation

Cost Forecasting Resource Allocation

See problems before they happen

For Providers

For Payers

For Regulators

USEFUL LINKS

CONTACT

AI-driven risk assessment for early disease detection,
proactive care, and improved health outcomes

Early Disease
Detection

Identify Risks
Intervene Early

Anticipate Risks
Reduce Complications

Cost Forecasting
Resource Allocation