The relationship between single nucleotide polymorphisms (SNPs) and phenotypes is noisy and cryptic due to the abundance of genetic factors and the influence of environmental factors on complex traits, which makes the idea of applying artificial neural networks (ANNs) as universal approximates of complex functions promising. In this study, we compared different ANN architectures and input parameters to predict the adult length of Pacific lampreys, which is the primary indicator of their total migratory distance. Feedforward and simple recurrent network architectures with a different range of input parameters and different sizes of hidden layers were compared. Results indicate that the highest performing ANN had an accuracy of 67.5% in discriminating between long and short specimens. Sensitivity and specificity were 62.16% and 70.73%, respectively. Our results imply that feedforward ANN architecture with a single hidden neuron is enough to solve the problem of specimen classification. Nonetheless, while ANNs are useful at approximating functions with unknown relationships in the case of SNP data, additional work needs to be performed to ensure that the chosen SNP markers are related to functional regions related to the examined trait, as the use of non-specific markers will result in the introduction of noise into the dataset.

Medical devices with measuring functions play a crucial role in diagnostics and treatment of patients is health care establishments. Both the testing and manufacturing guidelines laid out in the medical devices directive MDD 93/42, as well as the recommendations for electrical medical equipment in IEC 60601 and IEC 62353 are largely not implemented. The majority of the guidelines that are being followed are those relating to the manufacturing and selling (as well as obtaining of the CE mark), while the precision and accuracy of medical devices in the subsequent period of use are not sufficiently monitored. The manufacturers, distributors and servicing companies do provide yearly service to those contracted establishments. However, while the aforementioned service includes part replacement, it does not include measurements of output parameters which are of vital interest to the patients. Part of the reason for the lack of focus on exit parameters by the servicing companies is that they do not possess the necessary equipment needed to perform said tasks, thereby compromising the entire process of preventative maintenance. Due to the aforementioned, in order to regulate this domain, state agencies and the affiliated measurement laboratories ought to perform independent inspection (verification) of medical devices with measurement functions according to ISO 17020 standards. This would effectively abolish the lobby and monopoly that manufacturing companies hold over medical device repair and thereby not only lower the cost due to unnecessary servicing, but it would ensure an increase in medical device reliability and safety and ultimately patient diagnosis and treatment.