The enhanced advanced deep learning techniques for data analysis big data are a buzzword in the modern information technology industry that works in the healthcare sector and is an acronym in the field of medical research. The use of big data in medicine is the foundation of the contemporary health sector. The terms “big data” and “deep learning” are buzzwords that are commonly used in the healthcare sector. Electronic health records, medical imaging, prescription drugs, medical records, disease prediction, diagnosis and treatment patterns, remote consultations, and other medical services are all included in the big data. Software services for cloud computing power this massive amount of data. The primary idea and method applied in this case is machine learning. This technique makes it easier to interact with other collected records and allows for the creation of more diverse models. To improve the healthcare industry, big data requires enormous amounts of data processing and administration. The use of deep learning techniques for healthcare informatics using EHRs in various clinical activities was the exclusive focus of this research project. There are numerous clinical applications of deep learning techniques, such as data extraction, outcome prediction, and de-identification. A number of flaws in current studies have been discovered, including model interpretability and data heterogeneity. Additionally, we focused on deep learning prediction strategies for various diseases, as well as new progress in deep learning techniques in the domain of precision medicine and next-generation health care.