Internet of Things (IoT) has emerged as the fastest developing technology in the field of computing where connectivity among various types of devices is unified. Accessibility, adaptability, portability, and energy efficiency have made IoT technology applicable to various fields such as wearable devices, smart cities, smart homes, smart vehicles, agriculture, supply chain, and retail. IoT also plays an important role in the healthcare domain that mitigates the limitation of traditional healthcare facilities. IoT-based healthcare systems have been applied to monitor real-time human activities, which keep track of the records of patients. The latest advancements in the field of deep learning (DL) allow us to work with complex data without performing feature engineering on the IoT-enabled data collected from health service applications. In this chapter, we present a detailed discussion on IoT-based healthcare systems using different case studies with respect to DL models. More specifically, we discuss the recent trends, scopes, prospects, challenges, and limitations, and provide future research directions of DL in IoT-based healthcare systems. The rest of this chapter is organized as follows. Section 9.1 provides an introduction of the IoT and DL technologies with respect to various application domains. Section 9.2 details the relation of healthcare and IoT from an application perspective. Section 9.3 presents prospects of DL in healthcare. Section 9.4 discusses the challenges of IoT analytics in healthcare applications. Section 9.5 presents DL techniques in healthcare applications in detail. Finally, we conclude and discuss future works in Section 9.6.