Abstract
Healthcare systems worldwide are facing growing pressure from the rising prevalence of chronic diseases, increasing treatment costs, and unequal access to care. As the focus shifts from reactive treatment to preventive healthcare, early detection is emerging as a critical tool for improving patient outcomes and reducing long-term healthcare burden. Advances in artificial intelligence, retinal diagnostics, telemedicine and connected healthcare platforms are enabling faster, more accessible and non-invasive screening methods, helping identify systemic diseases at earlier stages and supporting timely intervention.
Keywords: Early Detection; Preventive Healthcare; Artificial Intelligence; Retinal Diagnostics; Digital Health; Oculomics.
Introduction
Healthcare systems are facing an increasingly complex challenge globally. The changing lifestyles are contributing to the growing prevalence of chronic diseases. With rising healthcare costs, an aging population and unequal access to care, immense pressure is building on the efficiency of healthcare infrastructure.
According to the World Health Organization, non-communicable diseases (NCDs), including cardiovascular diseases, diabetes, cancer and chronic respiratory conditions, account for nearly 75% of all deaths globally.1 In India, the burden is particularly significant, with over 100 million people living with diabetes.2 Working middle-class Indians often face the greatest financial vulnerability when it comes to healthcare. While they typically fall outside the eligibility criteria for government-supported schemes such as Ayushman Bharat, rising medical costs and escalating insurance premiums can make comprehensive healthcare coverage increasingly difficult to access. For many families, a single major medical emergency can still result in significant financial strain despite growing public investment in healthcare. Our healthcare sector must evolve from a reactive model focused on treatment to a proactive model cantered on prediction and prevention. Early detection is the most effective and underutilised step to be adopted by the healthcare ecosystem across the world.
Why Early Detection Matters
The consequences of delayed diagnosis extend far beyond individual patient outcomes. Diseases identified at advanced stages often require complex interventions demanding long-term medication, hospitalisation and extensive rehabilitation. This not only increases healthcare expenditure but also impacts family security and overall economic growth.
For example, systemic health conditions such as diabetes, hypertension and CVD can progress silently for years before symptoms become noticeable. By the time patients notice and seek medical attention, irreversible damage may already have occurred.3 Early detection allows individuals to seek guidance from healthcare providers, enabling them to intervene before it’s too late. These can be achieved through lifestyle modifications, regular monitoring or targeted treatment strategies that are significantly less resource-intensive than managing advanced disease. With specialist doctors concentrated in cities and metros, scalable screening programs are becoming essential components of public health strategies.
Technology Driving Preventive Healthcare
Technology is accelerating the shift toward prevention. Advances in artificial intelligence (AI), digital diagnostics, telemedicine and connected healthcare platforms are making early detection more accessible.4 Emerging fields such as Oculomics are harnessing this potential by combining high-resolution ocular imaging with advanced AI algorithms to uncover hidden biological indicators linked to Cardiovascular disease, Diabetes, Hypertension, Stroke, Alzheimer and other systemic conditions.
Traditionally, diagnosing systemic conditions required invasive methods like laboratory blood tests, followed by multiple clinical visits. Today, advancements in AI-powered retinal diagnostics are enabling us to estimate critical health indicators, including systemic conditions, through a simple retinal scan that takes only a few seconds.5 By analysing subtle patterns in retinal blood vessels, vessel density and microvascular behaviour, AI can provide valuable insights into an individual’s health status, often years before clinical symptoms become visible and begin to affect their daily life.
Expanding Access Through AI-Powered Diagnostics
The advancement of technology and AI is reshaping the healthcare landscape in countries like India, where access to specialist care remains a challenge in many regions. Portable diagnostic technologies, combined with AI-assisted analysis, are enabling healthcare providers to bring screening services closer to communities.
The future of healthcare will not be defined solely by our ability to treat disease, but by our ability to prevent it. At Forus Health, we have been committed to this vision by integrating AI into ocular diagnostics to prevent blindness and improve global access to healthcare. Our AI-powered diagnostic devices are designed to be portable, easy to operate and deployable even in rural and remote communities. Trained technicians can perform screenings locally, while specialists located hundreds of kilometres away can review results and provide clinical guidance through our digital health platform, FH TeleCare.
FH-POISE™, our advanced suite of AI models that supports screening, detection, diagnosis and disease management. Designed to augment clinical decision-making rather than replace clinicians, FH-POISE™ improves efficiency and accuracy across every stage of patient care. Through extensive R&D and validation across more than 500,000 screenings in diverse environments, the platform has demonstrated its reliability in assessing both ocular and systemic disease.
Conclusion
The convergence of AI-driven diagnostics and connected care is transforming healthcare from reactive intervention to proactive prevention, where a few minutes of retinal imaging can unlock critical insights into overall health.
References
- WHO [online]. Noncommunicable Diseases. Sep 2025. Available from https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases
- Chauhan S, Khatib MN, Ballal S, Bansal P, Bhopte K, Gaidhane AM, et al. The rising burden of diabetes and state-wise variations in India: insights from the Global Burden of Disease Study 1990-2021 and projections to 2031. Front Endocrinol (Lausanne). 2025 May 12;16:1505143.
- Nethan S, Sinha D, Mehrotra R. Non Communicable Disease Risk Factors and their Trends in India. Asian Pac J Cancer Prev. 2017 Jul 27;18(7):2005-2010.
- Fahim YA, Hasani IW, Kabba S, Ragab WM. Artificial intelligence in healthcare and medicine: clinical applications, therapeutic advances, and future perspectives. Eur J Med Res. 2025 Sep 23;30(1):848.
- Iorga RE, Costin D, Munteanu-Dănulescu RS, Rezuș E, Moraru AD. Non-Invasive Retinal Vessel Analysis as a Predictor for Cardiovascular Disease. J Pers Med. 2024 May 9;14(5):501.
