This paper presents an energy optimization approach to applying electrical impedance tomography (EIT) for medical diagnostics, particularly in detecting lung diseases. The designed Lung Electrical Tomography System (LETS) incorporates 102 electrodes and advanced image reconstruction algorithms. Energy efficiency is achieved through the use of modern electronic components and high-efficiency DC/DC converters that reduce the size and weight of the device without the need for additional cooling. Special attention is given to minimizing energy consumption during electromagnetic measurements and data processing, significantly improving the system’s overall performance. Research studies confirm the device’s high energy efficiency while maintaining the accuracy of the classification of lung disease using the LightGBM algorithm. This solution enables long-term patient monitoring and precise diagnosis with reduced energy consumption, marking a key step towards sustainable medical diagnostics based on EIT technology.