In the present scenario, there is a rapid development in the field of designing efficient medical devices for advanced health care purposes. A distinct hybrid fractal approach for designing tree-shaped antenna using artificial neural network (ANN) and particle swarm optimization is explored in this research paper. ANN modelling provides a promising solution, especially for solving various problems that are usually encountered in science and engineering. A Koch–like structure is added to a Giuseppe Peano-like structure for the construction of a parent hybrid shape. The overall volume of the FR4 based designed prototype is 24 x 20 x 1.6 mm 3 . The tree-like geometry is excited by a microstrip line feed, placed at the centre axis of the selected substrate. The ground plane dimension ‘L g ’ has been optimized specifically with particle swarm optimization technique. To realize the effectiveness of the hybrid fractal approach, the projected antenna is experimentally analyzed. The designed structure is compact, geometrically appealing and offers sufficient bandwidth. The projected antenna operates over 2.41 to 2.44 GHz, with fundamental frequency of 2.42 GHz. The S11 ≤ -10 dB bandwidth examined at the working frequency is 1.44% (35.1 MHz). Moreover, the projected antenna offers promising gain and stable radiation patterns at the claimed frequency. A simplified ANN strategy is also utilized for the estimation of selected output parameters. For completeness, simulated, estimated, optimized and experimental responses are reported to examine the reliability of the proposed hybrid fractal approach. Furthermore, the performance is effectively described by analyzing the behavior of projected antenna with different excitation methods. Excellent outcomes validate that this compact device makes it an ideal choice for bimedical applications.