Combined Artificial Intelligence Approaches Analyzing 1000 Conservative Patients with Back Pain-A Methodological Pathway to Predicting Treatment Efficacy and Diagnostic Groups.

Patients with back pain are common and present a challenge in everyday medical practice due to the multitude of possible causes and the individual effects of treatments. Predicting causes and therapy efficien cy with the help of artificial intelligence could improve and simplify the treatment. In an exemplary collective of 1000 conservatively treated back pain patients, it was investigated whether the prediction of therapy efficiency and the underlying diagnosis is possible by combining different artificial intelligence approaches. For this purpose, supervised and unsupervised artificial intelligence methods were analyzed and a methodology for combining the predictions was developed. Supervised AI is suitable for predicting therapy efficiency at the borderline of minimal clinical difference. Non-supervised AI can show patterns in the dataset. We can show that the identification of the underlying diagnostic groups only becomes possible through a combination of different AI approaches and the baseline data. The presented methodology for the combined application of artificial intelligence algorithms shows a transferable path to establish correlations in heterogeneous data sets when individual AI approaches only provide weak results.

Constructed wetlands--Are they safe in reducing protozoan parasites?

Constructed wetlands have been promoted in recent literature for use in rural communities in developed as well as in developing countries as an appropriate technology to be handled with low operational maintenance costs. Within a joint project supported by BMBF (Project No O2WA0107 and No 02WA0108) research was done concerning the sanitation effect of constructed wetlands on wastewater effluents. This article will focus on the detection and the removal of cysts of Cryptosporidium parvum and Giarda lamblia, those being the most frequently identified pathogenic protozoan parasites worldwide with increasing medical and economical consequences. Two plants, one installed in 2000 as a pilot plant at Langenreichenbach near Leipzig (Saxony, Germany), the other one in routine operation since 1993 in a training center at the town of Belzig (Brandenburg, Germany) were tested for three years. Detection methods from the US EPA (ICR Protozoan Method for Detecting Giardia Cysts and Cryptosporidium Oocysts in Water by a Fluorescent Antibody Procedure (EPA/814-B-95-003;US EPA 1995) were employed in order to assess protozoal and bacterial reduction in the wastewater passing through different combinations of filter beds and fillings. Removal of cysts of Cryptosporidium and Giardia spp. turned out to be a 2 log reduction in all plants. The most effective structural element was a two-stage combination of filter beds leading to the highest removal efficiency both for the protozoan and the bacterial indicator organisms. Also, washed sand (0-2mm grain size) in the filter bed proved to be most effective filter material; the planted reed (phragmites spp.) or willow (salix spp.), however, turned out to be of minor importance for the filtering activity.