This research focuses on the analysis of applying enhanced forms of artificial intelligence in improving management information system in healthcare. By analyzing various methods of machine learning, deep learning, NLP, and IoT analytics, carrying out their analysis, as well as their practical application, the given work sheds light on their revolutionary role in health care. Some of the identified works involved the use of Random Forests and Convolutional Neural Networks Clinicians, achieving prediction accuracy of 85 % and 92 % respectively in two clinical decision support and Medical image analysis tasks. In this study, to analyze entity recognition, the NER process was supported by CRF and achieved an 88 % F1-score for identifying medical entities in textual data, increasing the speed of clinical documentation. Moreover, IoT based anomaly detection systems obtained a 95% of the detection rate contributing to the improvement of real time observation and urgent response into the healthcare environments.