The scientific community has widely recognized thermosensitive hydrogels as highly biocompatible material with immense potential in drug delivery systems. When the temperature of these hydrogels approaches that of human body, a phase change occurs, enhancing their usefulness in a range of medical scenarios. This review article highlighted the background of thermosensitive hydrogels, their properties, and their applications in transdermal, oral, ophthalmic, intravaginal, nasal, rectal, cancer therapy, and cell‐loaded drug delivery systems. The literature suggests numerous advantages of these hydrogels over conventional drug delivery systems and find applications in various fields, such as therapeutic systems, filling processes, and sustained drug delivery systems. One of their key benefits is the ability to eliminate invasive procedures like surgery, providing a noninvasive alternative for drug administration. Moreover, they streamline the formulation process for both hydrophilic and hydrophobic drug delivery systems, simplifying the development of effective treatments. The thermosensitive hydrogels have been found to be green materials with negligible side effects and desirable drug delivery properties. The thermosensitive hydrogel's sustained‐release characteristics, immunogenicity, and biodegradability have also gained increased interest. Some of the disadvantages of thermosensitive hydrogels include delayed temperature response, weak mechanical characteristics, and poor biocompatibility, which limits their potential use in drug delivery applications.

Wearable bioelectronics and therapeutics are a rapidly evolving area of research, with researchers exploring new materials that offer greater flexibility and sophistication. Conductive hydrogels have emerged as a promising material due to their tunable electrical properties, flexible mechanical properties, high elasticity, stretchability, excellent biocompatibility, and responsiveness to stimuli. This review presents an overview of recent breakthroughs in conductive hydrogels, including their materials, classification, and applications. By providing a comprehensive review of current research, this paper aims to equip researchers with a deeper understanding of conductive hydrogels and inspire new design approaches for various healthcare applications.

The rapid expansion of miniature biomedical devices has attracted considerable global attention, driven by the growing demand for advanced healthcare solutions. Despite significant progress in materials, fabrication techniques, and device architectures that have propelled the development of wearable and implantable technologies, a critical challenge remains: mimicking the structure and function of human skin. This challenge contrasts advancements in power efficiency, design miniaturization, precision, and device integration. Recent breakthroughs in manufacturing techniques and the development of high‐performance organic and inorganic piezoelectric materials with tunable mechanical properties offer transformative potential to overcome these limitations. This review systematically examines the evolution of piezoelectric materials for health monitoring applications, focusing on their historical development, underlying mechanisms, fabrication strategies, and characterization techniques. We critically evaluate their integration into wearable and implantable systems, emphasizing their potential to address power autonomy, device adaptability, and sensing accuracy issues. Additionally, the article highlights emerging interdisciplinary research frontiers in bioengineering, highlighting pioneering contributions from global research teams. By synthesizing key advancements and identifying unresolved challenges, this review aims to provide a comprehensive guide for future innovations in smart biomedical devices, fostering collaborative efforts across the materials science, electronics, and healthcare fields.

Background: Lung cancer is one of the most fatal cancers worldwide, and malignant tumors are characterized by the growth of abnormal cells in the tissues of lungs. Usually, symptoms of lung cancer do not appear until it is already at an advanced stage. The proper segmentation of cancerous lesions in CT images is the primary method of detection towards achieving a completely automated diagnostic system. Method: In this work, we developed an improved hybrid neural network via the fusion of two architectures, MobileNetV2 and UNET, for the semantic segmentation of malignant lung tumors from CT images. The transfer learning technique was employed and the pre-trained MobileNetV2 was utilized as an encoder of a conventional UNET model for feature extraction. The proposed network is an efficient segmentation approach that performs lightweight filtering to reduce computation and pointwise convolution for building more features. Skip connections were established with the Relu activation function for improving model convergence to connect the encoder layers of MobileNetv2 to decoder layers in UNET that allow the concatenation of feature maps with different resolutions from the encoder to decoder. Furthermore, the model was trained and fine-tuned on the training dataset acquired from the Medical Segmentation Decathlon (MSD) 2018 Challenge. Results: The proposed network was tested and evaluated on 25% of the dataset obtained from the MSD, and it achieved a dice score of 0.8793, recall of 0.8602 and precision of 0.93. It is pertinent to mention that our technique outperforms the current available networks, which have several phases of training and testing.