Empowering Healthcare with AI: Advancements in Medical Image Analysis, Electronic Health Records Analysis, and AI-Driven Chatbots

The integration of Artificial Intelligence (AI) into healthcare has ushered in a new era of transformative advancements, addressing critical aspects such as Medical Image Analysis (MIA), Electronic Health Records (EHR), and AI-driven Chatbots. In this research paper, we present comprehensive developments in these domains, demonstrating their synergistic potential. In the realm of Medical Image Analysis, we have employed transfer learning techniques and harnessed diverse datasets, which include Pneumonia Chest X-Ray Images, and the Tuberculosis (TB) Chest X-ray Database, and the bone cancer Chest X-ray Database. Our models, built using transfer learning, have achieved remarkable accuracy, with some reaching an impressive 98.4% on the datasets collected from various sources. Notably, among the selected models, including InceptionV3, InceptionResNetV2, DenseNet121, DenseNet169, DenseNet201, ResNet50V2, ResNet101V2, VGG16, and VGG19. DenseNet201 has displayed exceptional performance, attaining an accuracy of 98.4%. The proposed work encapsulates significant advancements in AI within the healthcare domain, particularly in the fields of Medical Image Analysis, Electronic Health Records, and AI-driven Chatbots. Through rigorous experimentation and innovation, we demonstrate the potential to reshape healthcare delivery, diagnosis, and patient engagement. These developments underscore the transformative power of AI in redefining the healthcare landscape for the better.