V1I5P4

Post Cataract Surgery Complication Detection System 

Ukabuiro Ikenna Kelechi^1*, Odikwa H.N¹, Agomah S.A¹

Abstract

The paper on post cataract surgery complication detection system presents a comprehensive system designed to improve the outcomes and post-operative management of cataract surgery. The system integrates predictive analytics, complication detection, and patient-centred features to support both healthcare providers and patients throughout the cataract surgery journey. Using machine learning algorithms, the system predicts the likely outcomes of cataract surgery based on patient-specific data such as age, medical history, and visual acuity results. After the development of the cataract detection system, it was deployed in hospitals and patients tested with system and analysis done on the outcome. The methodology used for analysis was Object-Oriented Analysis Design and Methodology, the languages used to build the system were; HTML, CSS, PHP. Results were obtained, and the system demonstrated an accuracy of 85% in identifying potential complications, 90% of patients reported that the guidelines were clear and helpful in preparing for surgery and managing post-operative care, 88% of patients reported that the reminder feature was helpful in maintaining their post-surgery eye drop schedule. The effectiveness of the system’s pre- and post-surgery guidelines was assessed through patient surveys and clinical outcomes. The outcome shows 90% of patients reported that the guidelines were clear and helpful in preparing for surgery and managing post-operative care.

Keywords:

Post-cataract; lens; detection system