Neural networks as a prognostic tool in critically ill patients

Im Zeitraum 1. 11. 1993 bis 30. 3. 1997 wurden 1149 allgemeinchirurgische Intensivpatienten prospektiv erfaßt, von denen 114 die Kriterien des septischen Schocks erfüllten. Die Letalität der Patienten mit einem septischen Schock betrug 47,3%. Nach Training eines neuronalen Netzes mit 91 (von insgesamt n = 114) Patienten ergab die Testung bei den verbleibenden 23 Patienten bei der Berücksichtigung von Parameterveränderungen vom 1. auf den 2. Tag des septischen Schocks folgendes Ergebnis: Alle 10 verstorbenen Patienten wurden korrekt als nicht überlebend vorhergesagt, von den 13 Überlebenden wurden 12 korrekt als überlebend vorhergesagt (Sensitivität 100%; Spezifität 92,3%).Neural networks as a prognostic tool in critically ill patients Summary: From 1. 11. 93 to 30. 3. 97, 1149 patients were prospectively studied during their ICU stay. Of them,114 met the criteria of septic shock, with lethality of 47.3%. A neural network was trained with datasets from 91 of these 114 patients. Testing the trained neural network with the remaining 23 patients, the following result was obtained: all 10 patients dying from septic shock were correctly predicted; of 13 surviving patients, 12 were correctly identified (sensitivity 100%; specifity 92.3%)

A Hybrid N-body--Coagulation Code for Planet Formation

We describe a hybrid algorithm to calculate the formation of planets from an initial ensemble of planetesimals. The algorithm uses a coagulation code to treat the growth of planetesimals into oligarchs and explicit N-body calculations to follow the evolution of oligarchs into planets. To validate the N-body portion of the algorithm, we use a battery of tests in planetary dynamics. Several complete calculations of terrestrial planet formation with the hybrid code yield good agreement with previously published calculations. These results demonstrate that the hybrid code provides an accurate treatment of the evolution of planetesimals into planets.Comment: Astronomical Journal, accepted; 33 pages + 11 figure

A hemispheric two-channel code accounts for binaural unmasking in humans

The ability to localize sound sources relies on differences between the signals at the two ears. These differences are also the basis for binaural unmasking, an improvement in detecting or understanding a sound masked by sources from other locations. The neurocomputational operation that underlies binaural unmasking is still a matter of debate. Current models rely on the cross-correlation function of the signals at the two ears, the neuronal substrate of which has been observed in the barn owl but not in mammals. This disagreement lead to the formulation of an alternative coding mechanism where interaural differences are encoded using the neuronal activity within two hemispheric channels. This mechanism agrees with mammalian physiology but has not yet been shown to account for binaural unmasking in humans. This study introduces a new mathematical formulation for the two-channel model, which is then used to explain the outcome of an extensive library of psychoacoustic experiments

A hemispheric two-channel code accounts for binaural unmasking in humans

Sound in noise is better detected or understood if target and masking sources originate from different locations. Mammalian physiology suggests that the neurocomputational process that underlies this binaural unmasking is based on two hemispheric channels that encode interaural differences in their relative neuronal activity. Here, we introduce a mathematical formulation of the two-channel model – the complex-valued correlation coefficient. We show that this formulation quantifies the amount of temporal fluctuations in interaural differences, which we suggest underlie binaural unmasking. We applied this model to an extensive library of psychoacoustic experiments, accounting for 98% of the variance across eight studies. Combining physiological plausibility with its success in explaining behavioral data, the proposed mechanism is a significant step towards a unified understanding of binaural unmasking and the encoding of interaural differences in general

Statistics of the interaural parameters for dichotic tones in diotic noise (N0SψN_0 S_\psi)

Stimuli consisting of an interaurally phase-shifted tone in diotic noise -- often referred to as $N_0 S_\psi$ -- are commonly used in the field of binaural hearing. As a consequence of mixing diotic noise with a dichotic tone, this type of stimulus contains random fluctuations in both interaural phase- and level-difference. This study reports the joint probability density functions of the two interaural differences as a function of amplitude and interaural phase of the tone. Furthermore, a second joint probability density function for interaural phase differences and the instantaneous power of the stimulus is derived

Social Justice in Healthcare: Access & Equity

This poster defines social justice in healthcare, addressing access and equity from local, national, and global perspectives. It explores solutions from local, national, and global perspectives as well, acknowledging biases surrounding the subject. Exploring it from these three perspectives raises awareness of the ways in which diverse populations have been affected, resulting in disparities in healthcare, ultimately leading to extensive gaps in education and resources. This project looks at the greater Bridgeport community, the overall United States, and healthcare accessibility worldwide. It discusses barriers faced by those that are poor and marginalized, and solutions that have potential to create great change. This project is utilized to gain a deeper understanding, and provides education and solutions that will assist in reducing social injustices within the healthcare system

EXPERIMENTAL INVESTIGATION OF THIN-WALLED CYLINDRICAL CANTILEVER BEAMS UNDERGOING VORTEX-INDUCED VIBRATIONS

M.S

Comparison of Multi-Compartment Cable Models of Human Auditory Nerve Fibers

Background: Multi-compartment cable models of auditory nerve fibers have been developed to assist in the improvement of cochlear implants. With the advancement of computational technology and the results obtained from in vivo and in vitro experiments, these models have evolved to incorporate a considerable degree of morphological and physiological details. They have also been combined with three-dimensional volume conduction models of the cochlea to simulate neural responses to electrical stimulation. However, no specific rules have been provided on choosing the appropriate cable model, and most models adopted in recent studies were chosen without a specific reason or by inheritance. Methods: Three of the most cited biophysical multi-compartment cable models of the human auditory nerve, i.e., Rattay et al. (2001b), Briaire and Frijns (2005), and Smit et al. (2010), were implemented in this study. Several properties of single fibers were compared among the three models, including threshold, conduction velocity, action potential shape, latency, refractory properties, as well as stochastic and temporal behaviors. Experimental results regarding these properties were also included as a reference for comparison. Results: For monophasic single-pulse stimulation, the ratio of anodic vs. cathodic thresholds in all models was within the experimental range despite a much larger ratio in the model by Briaire and Frijns. For biphasic pulse-train stimulation, thresholds as a function of both pulse rate and pulse duration differed between the models, but none matched the experimental observations even coarsely. Similarly, for all other properties including the conduction velocity, action potential shape, and latency, the models presented different outcomes and not all of them fell within the range observed in experiments. Conclusions: While all three models presented similar values in certain single fiber properties to those obtained in experiments, none matched all experimental observations satisfactorily. In particular, the adaptation and temporal integration behaviors were completely missing in all models. Further extensions and analyses are required to explain and simulate realistic auditory nerve fiber responses to electrical stimulation