KidneyLifePlus+ : Retinal Imaging Analysis for Kidney Disease Risk Assessment
Chronic kidney disease (CKD) represents a significant public health challenge, often referred to as a “silent disease” due to its asymptomatic progression during early stages (1–2). Consequently, most diagnoses occur during advanced stages (3 and beyond), where treatment options are more complex and outcomes are less favorable. Globally, CKD affects over 850 million individuals, with 434.3 million cases in Asia alone. Despite its prevalence, early-stage awareness remains alarmingly low, with only 5% of affected individuals aware of their condition. Existing screening methods are predominantly hospital-based, expensive, and time-intensive, limiting their accessibility, particularly in resource-constrained settings. This underscores an urgent need for more accessible and efficient diagnostic tools to enable early intervention. In response to this critical problem, we developed KidneyLifePlus+, an AI-powered platform that leverages advanced machine learning models, including U-net, ResNet-50, and YOLO v8, to analyze retinal images for early CKD detection. These models are integrated to ensure high screening accuracy by identifying subtle biomarkers indicative of CKD progression. Complementing the software, we designed proprietary hardware capable of capturing high-resolution retinal images, delivering performance comparable to hospital-grade equipment. By ensuring affordability and ease of use, the system extends screening capabilities beyond clinical environments, making it suitable for deployment in community healthcare settings. KidneyLifePlus+ addresses key limitations of traditional methods by offering a rapid, cost-effective, and highly accurate diagnostic solution. The platform’s potential to enhance early detection rates could significantly improve clinical outcomes and quality of life for CKD patients. Furthermore, this innovation contributes to global efforts to reduce the burden of CKD by promoting equitable access to diagnostic services, particularly in underserved regions.
Production of Nano-Composite Artificial Bone Tissue Using Bioceramic Synthesis from Bio-Waste
Certain specially structured ceramics, which can be used as biomaterials to replace bone, have recently started being utilized in the medical field. The aim of this study is to produce high-bioactivity silica from corn cob waste, a widely available organic material in nature, and combine it with calcium oxide (CaO) obtained by grinding organic mussel shell waste with high bioactivity. This combination is intended to synthesize dicalcium silicate (2CaO.SiO₂) to develop an alternative tissue scaffold with high bioactivity, capable of replacing bone, for existing titanium alloys. The goal is to incorporate this scaffold into PEEK (polyether ether ketone), a novel tissue scaffold material, at varying percentages to create a next-generation innovative bone substitute material. An additional objective is to demonstrate through biocompatibility tests that the produced ceramic-polymer biocomposite exhibits antibacterial activity against Staphylococcus aureus.