This study evaluates the use of bioimpedance spectroscopy (BIS) as a non-invasive method to assess the freshness of fruits and vegetables by measuring impedance, its components, and phase angle. Over nine days, three vegetables (potato, pumpkin, and red pepper) and two fruits (apple and banana) were assessed using the Analog Discovery 3 device, covering a frequency range of 50 Hz to 1 MHz. The results showed a consistent decrease in impedance and an increase in phase angle during ripening, with statistical significance observed for pumpkin and potato (p < 0.05). The findings confirm BIS as an effective, objective, and non-destructive alternative to traditional chemical methods for monitoring freshness, despite challenges such as structural damage in red pepper. This integration of BIS into food quality assessment and healthcare provides a multidisciplinary approach to improving nutrition and health.

The COVID-19 pandemic caused a sharp increase in the interest in artificial intelligence (AI) as a tool supporting the work of doctors in difficult conditions and providing early detection of the implications of the disease. Recent studies have shown that AI has been successfully applied in the healthcare sector. The objective of this paper is to perform a systematic review to summarize the electroencephalogram (EEG) findings in patients with coronavirus disease (COVID-19) and databases and tools used in artificial intelligence algorithms, supporting the diagnosis and correlation between lung disease and brain damage, and lung damage. Available search tools containing scientific publications, such as PubMed and Google Scholar, were comprehensively evaluated and searched with open databases and tools used in AI algorithms. This work aimed to collect papers from the period of January 2019–May 2022 including in their resources the database from which data necessary for further development of algorithms supporting the diagnosis of the respiratory system can be downloaded and the correlation between lung disease and brain damage can be evaluated. The 10 articles which show the most interesting AI algorithms, trained by using open databases and associated with lung diseases, were included for review with 12 articles related to EEGs, which have/or may be related with lung diseases.