A Survey on Artificial Intelligence Techniques for Disease Prediction in Healthcare

The rapid advancement of medical data and the ever-increasing need for effective healthcare services are causing a major shift in the healthcare industry. Clinical reports, wearable devices, medical imaging, and electronic health records all generate massive amounts of data that traditional data analysis tools may struggle to process. Artificial intelligence (AI) is a powerful technology that may help medical professionals analyze complex healthcare data and improve the quality of diagnosis and treatment. In particular, the use of AI, which encompasses ML, DL, and NLP, has shown immense promise in the realm of disease prediction and the discovery of previously unseen patterns in patient data. Early detection of cardiovascular disease, diabetes, cancer, and neurological problems also allows for better treatment results and more timely decision-making. This in-depth analysis of AI's role in healthcare covers a wide range of disease prediction algorithms, including CNNs, SVMs, Decision Trees, RF, and ANN. Integration of AI with the internet of things (AIoT) for health monitoring is also included in the research, along with diagnosis and prognosis. It highlights the fundamental challenges of data quality, privacy, and explain ability of AIoT models in healthcare equipment.