Game-Changing AI for Eye Care: Dr. Poranki’s Research Redefines Diabetic Retinopathy Screening

Sandy, UT – 2025 – A transformative leap in healthcare AI has emerged from the pioneering research of Dr. Venkata Kotam Raju Poranki (PVK), Ph.D., whose latest work is reshaping the landscape of diabetic retinopathy (DR) diagnosis. Leveraging cutting-edge artificial intelligence frameworks, Dr. Poranki’s innovations offer hope to millions at risk of vision loss, particularly in underserved rural communities.

With over 460 million people worldwide living with diabetes, diabetic retinopathy remains a leading cause of preventable blindness. The traditional diagnostic process—manual analysis of retinal images by ophthalmologists—is often slow, expensive, and inaccessible in remote regions. Dr. Poranki’s AI-driven solution is poised to solve these challenges by delivering faster, more accurate, and privacy-conscious diagnostics.

A Groundbreaking AI Architecture for Vision Preservation

Dr. Poranki’s doctoral research at Koneru Lakshmaiah Education Foundation led to the development of four interconnected AI frameworks: DRG-Net, CEFNet, SDRG-Net, and ICNN-IRDO. Each system is uniquely designed to address persistent limitations in retinal image analysis and diagnostic scalability.

• DRG-Net enhances classification by integrating graph-based feature extraction with XGBoost, addressing dataset imbalances and improving overall accuracy.
• CEFNet employs an Iterative Random Forest approach for better feature refinement and robust performance on diverse data sets.
• SDRG-Net ensures data privacy through Multi-Level Color Transformation (MLCT) encryption and employs a disease-specific graph correlation network for precision grading.
• ICNN-IRDO combines deep learning with intelligent optimization algorithms, enabling generalized performance across various clinical environments.

Together, these frameworks form a comprehensive pipeline capable of automating both detection and grading of diabetic retinopathy in real time—without compromising data security.

Clinical Accuracy Backed by Real-World Validation

Dr. Poranki’s models were rigorously tested on benchmark datasets including EyePACS and Messidor, where they delivered astounding performance: 99.7% accuracy, with 100% sensitivity and specificity. These results not only surpass current industry standards but also ensure minimal false positives or negatives—critical in life-altering diagnoses like DR.

The innovations have been validated through peer-reviewed publications in Elsevier, Informatica and IEEE, and protected under design and utility patents in India, underscoring the originality and technical rigor of the research.

Bridging Innovation with Accessibility

More than academic excellence, what sets Dr. Poranki’s work apart is its direct applicability to real-world healthcare systems. These AI frameworks are currently being adapted into Internet of Medical Things (IoMT)-based kiosks, designed for deployment in rural India. Equipped with solar power, these units can:

• Capture high-resolution retinal images,
• Analyze them locally using the AI models,
• Transmit results securely to ophthalmologists via cloud networks.

This decentralization of diagnostics empowers early intervention, potentially saving the eyesight of millions who otherwise lack access to specialist care.

Pioneering Trustworthy AI in Healthcare

In an age where AI adoption in healthcare is often slowed by concerns over trust, bias, and data security, Dr. Poranki’s work sets a new benchmark. By combining graph learning, ensemble modeling, and privacy-preserving encryption, his frameworks are designed not only for accuracy but also for trustworthiness—a critical requirement for clinician and patient adoption.

This holistic approach ensures scalability and ethical compliance, offering a replicable model for AI integration in other medical domains as well.

About Dr. Venkata Kotam Raju Poranki (PVK)

With over 20 years of industry experience in software engineering and product innovation, Dr. Poranki currently serves as Program Manager at Zions Bank, Utah, USA, where he bridges the gap between academic research and practical implementation. His work spans secure healthcare and financial systems, driven by a mission to make AI-powered diagnostics affordable, ethical, and universally accessible.

Media Contact:

Dr. Venkata Kotam Raju Poranki (PVK), Ph.D.

7930 S 1000 E
Sandy, UT 84094, USA
+1 801 300 7949 (WhatsApp)
vporanki@gmail.com