An Intelligent IoT-Driven Diagnostic Platform for Cardiovascular and Dermatological Disease Detection with Machine Learning - Mudholkar, Pankaj; Mudholkar, Megha; Pal, Kaushika; Ramaprakash, Chitra; Behera, Snigdha Rani; Panda, Ribhu Abhusan (Journal of Neonatal Surgery, 2025)
The use of machine learning and IoT in diagnosing various diseases has improved through the provision of real-time and early diagnostic information. This paper will discuss a new, IoT-based, diagnostic system that could be used to diagnose both cardiovascular and dermatological disorders at the same time. The proposed platform leverages handcrafted features for the CVD diagnosis using deep neural networks in the ECG signals; as well as the real-time dermatological image analysis to improve the detection of skin cancer. Moreover, because of the adversarially robust model, the framework does not rely on perfect data and works well even in the conditions like noise or data loss. The adopted system design involves IoT devices with data acquisition, data processing, and data transmission to ensure round-the-clock patient monitoring and adequate diagnosis. Cardiovascular as well as dermatological domains also demonstrate the uses of ML and IoT on this platform to exhibit the fact that it would be capable of working on a number of healthcare fields. This paper aims to falling under the theme and realization of intelligent health monitoring systems through integrating latest technologies to aid in achieving a higher trajectory in diagnostics and thereby advancing patient care.