Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities

• Main Authors: Anichur Rahman (Author), Tanoy Debnath (Author), Dipanjali Kundu (Author), Md. Saikat Islam Khan (Author), Airin Afroj Aishi (Author), Sadia Sazzad (Author), Mohammad Sayduzzaman (Author), Shahab S. Band (Author)
• Format: Book
• Published: AIMS Press, 2024-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.3934/publichealth.2024004; 2327-8994
• Keywords: machine learning (ml); deep learning (dl); smart healthcare; internet of things (iot); feature extraction; data collection; data analysis; Public aspects of medicine; RA1-1270
• Source: AIMS Public Health, Vol 11, Iss 1, Pp 58-109 (2024)

In recent years, machine learning (ML) and deep learning (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications. Further, given the current progress in the fields of ML and DL, there exists the promising potential for both to provide support in the realm of healthcare. This study offered an exhaustive survey on ML and DL for the healthcare system, concentrating on vital state of the art features, integration benefits, applications, prospects and future guidelines. To conduct the research, we found the most prominent journal and conference databases using distinct keywords to discover scholarly consequences. First, we furnished the most current along with cutting-edge progress in ML-DL-based analysis in smart healthcare in a compendious manner. Next, we integrated the advancement of various services for ML and DL, including ML-healthcare, DL-healthcare, and ML-DL-healthcare. We then offered ML and DL-based applications in the healthcare industry. Eventually, we emphasized the research disputes and recommendations for further studies based on our