Development of a neuro-fuzzy technique for automated parameter optimization of inverse treatment planning

<p>Abstract</p> <p>Background</p> <p>Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy (IMRT) is mainly conducted by human planners in order to create a plan with the desired dose distribution. To automate this tedious process, an artificial intelligence (AI) guided system was developed and examined.</p> <p>Methods</p> <p>The AI system can automatically accomplish the optimization process based on prior knowledge operated by several fuzzy inference systems (FIS). Prior knowledge, which was collected from human planners during their routine trial-and-error process of inverse planning, has first to be "translated" to a set of "if-then rules" for driving the FISs. To minimize subjective error which could be costly during this knowledge acquisition process, it is necessary to find a quantitative method to automatically accomplish this task. A well-developed machine learning technique, based on an adaptive neuro fuzzy inference system (ANFIS), was introduced in this study. Based on this approach, prior knowledge of a fuzzy inference system can be quickly collected from observation data (clinically used constraints). The learning capability and the accuracy of such a system were analyzed by generating multiple FIS from data collected from an AI system with known settings and rules.</p> <p>Results</p> <p>Multiple analyses showed good agreements of FIS and ANFIS according to rules (error of the output values of ANFIS based on the training data from FIS of 7.77 ± 0.02%) and membership functions (3.9%), thus suggesting that the "behavior" of an FIS can be propagated to another, based on this process. The initial experimental results on a clinical case showed that ANFIS is an effective way to build FIS from practical data, and analysis of ANFIS and FIS with clinical cases showed good planning results provided by ANFIS. OAR volumes encompassed by characteristic percentages of isodoses were reduced by a mean of between 0 and 28%.</p> <p>Conclusion</p> <p>The study demonstrated a feasible way to automatically perform parameter optimization of inverse treatment planning under guidance of prior knowledge without human intervention other than providing a set of constraints that have proven clinically useful in a given setting.</p

The Effect of Music on the Anxiety of Mothers of Infants Admitted to the Neonatal Intensive Care Unit

BACKGROUND AND OBJECTIVE: Mothers with premature infants often experience a lot of anxiety, and since music has positive effects on anxiety, the present study was conducted to investigate the effect of music on the anxiety of mothers of infants admitted to the neonatal intensive care unit. METHODS: This clinical trial was performed on 120 mothers with infants admitted to the neonatal intensive care unit of Rouhani Hospital in Babol and Bu-Ali Sina Hospital in Sari. Samples were randomly divided into two groups of experimental and control each consisting of 60 patients. In the experimental group, relaxing music was played daily through mobile phones and headphones for each mother individually for 10 minutes in 10 sessions. No intervention was performed for the control group. Both groups of mothers completed the Spielberger State-Trait Anxiety Inventory (STAI) before the start of the study and on the tenth day and were compared. FINDINGS: The mean age of mothers was 27.8±5.71 years and the mean age of infants was 3.92±3.88 days. In this study, anxiety was relatively severe or severe in 60% of mothers before the intervention. Levels of overt anxiety and covert anxiety in mothers of music groups before the intervention (59.48±13.66), (55.62±12.26) showed a significant decrease compared to after the intervention (31.27±6.57), (33.08±8.66), respectively (p<0.0001). CONCLUSION: The results of the study showed that music is effective in reducing the anxiety of mothers with infants admitted to the neonatal intensive care unit

Opposite effects of male and female helpers on social tolerance and proactive prosociality in callitrichid family groups

Across a broad variety of primate species (including lemurs, New World monkeys, Old World monkeys, and apes), proactive prosociality and social tolerance are linked to allomaternal care, reaching the highest levels in the cooperatively breeding callitrichid monkeys and humans. However, considerable variation exists within callitrichids, and the aim of this study was to identify factors that explain this variation. Male and female callitrichids pursue different reproductive strategies, leading males to play a more prominent role in allomothering. We thus hypothesised that prosociality and tolerance may be affected by group composition and sex differences. We analysed social tolerance and proactive prosociality data in 49 common marmosets and found that the number of female helpers in a group was negatively correlated with group-level prosociality and tolerance. At the individual level, rearing experience or age enhanced prosociality in male, but not in female helpers. These findings are consistent with the more ambivalent role of female helpers in infant rearing. Adding data from 5 cotton-top and 5 lion tamarins strengthened this pattern. The same factor which explains variation in prosociality and tolerance across primate species, i.e. allomaternal care, is therefore also linked to variation within common marmosets, and presumably callitrichid monkeys in general