Abstract Medical diagnosis is one of the most tedious and complex processes that healthcare per sonnel face in their day-to-day life. To establish an adequate treatment, it is essential to carry out a correct and early evaluation of each patient. Occasionally, given the number of tests that need to be performed, this evaluation process can require a significant amount of time, and can negatively affect the patient’s recovery. The objective of this work is the de velopment of a new software that, using Artificial Intelligence (AI), offers the healthcare professional support in the process of diagnosing the patient, as well as preventing the probability of suffering a certain disease, based on test information analytics and demo graphic information available. The system allows storing multiple models based on Deep Learning (DL), previously trained for the diagnosis of different diseases. These models allow predictions to be made based on available medical information. As a use case, one of these models has been successfully tested in diagnosing stroke events.

Abstract This study aims to confirm whether noncontact monitoring of relative changes in blood pressure can be estimated using microwave radar sensors. First, an equation to estimate blood pressure was derived, after which, the effectiveness of the estimation equation was confirmed using data obtained by a noncontact method while inducing variations in blood pressure. We considered that the Bramwell-Hill equation, which contains some parameters that directly indicate changes in blood pressure, would be an appropriate reference to con struct an estimation equation for the noncontact method, because measurements using mi crowave radar sensors can measure minute scale motion on the skin surface induced by the pulsation of blood vessels. In order to estimate relative changes in blood pressure, we con sidered a simple equation including the pulse transit time (PTT), amplitude of signals and body dimensions as parameters. To verify the effectiveness of the equation for estimating changes in blood pressure, two experiments were conducted: a cycling task using an ergo meter, which induces blood pressure fluctuations because of changes in cardiac output, and a task using the Valsalva maneuver, which induces blood pressure fluctuations because of changes in vascular resistance. The results obtained from the two experiments suggested that the proposed equation using microwave radar sensors can accurately estimate relative changes of blood pressure. In particular, relatively favorable results were obtained for the changes in blood pressure induced by the changes in cardiac volume. Although many issues remain, this method could be expected to contribute to the continuous evaluation of cardiac function while reducing the burden on patients.

Abstract Objective: To explore the consistency and relevance of the results of the bedside rapid blood gas analyzer GEM premier 3000, the Vitros5.1+5600 biochemical immunoassay analyzer and the SYSMEX XN-9000 automatic blood cell analyzer in the central laboratory detecting serum potassium (K+), serumsodium (Na+), blood glucose (Glu), hemoglobin (Hb) and red blood cell volume (Hct). And to provide a reference for the accurate interpretation of the bedside blood gas analysis report. Method: Usually, ICU patients will be taken arterial blood gas, biochemical and blood samples through the arterial indwelling needle; at the same time patients’ potassium, serum sodium, blood glucose, hemoglobin and red blood cell volume will be detected. This study implemented paired t-test and correlation regression analysis on each group of data, and used the analysis quality requirements (allowable total error) of CLIA’88 proficiency testing program as the criteria for clinical acceptance. Results: The paired t-test showed that the serum potassium, serum sodium and blood glucose detected by GEM premier 3000 and Vitros5.1+5600 were significantly different; and the hemoglobin and red blood cell volume detected by GEM premier 3000 and SYSMEX XN-9000 were sig nificantly different (P < 0.05). The Pearson correlation coefficients (r) of hemoglobin, red blood cell volume and red blood cell volume were 0.860, 0.886, 0.924, 0.841 and 0.856, re spectively, and the above test items all had good correlations (P < 0.05). The average (SE) of the paired differences of K+, Na+, Glu, Hb and Hct detected by the two sets of instruments is less than the allowable error of CLIA’88, and the SE of blood Na+ and Hb is less than half of the allowable error of CLIA’88. Conclusion: The test results of GEM premier 3000, the cen tral laboratory Vitros5.1+5600 and SYSMEX XN-9000 have good correlation, but the consistency is not good. The test results of GEM premier 3000 cannot replace the central labor atory.

Abstract Microtubules (MT) are of great engineering importance due to their potential applications as sensors, actuators, drug delivery, and others. The MT properties/mechanics are greatly affected by their biomechanical environment and it is important to understand their bio logical function. Although microtubule mechanics has been extensively studied statically, very limited studies are devoted to the biomechanical properties of microtubule undergoing deformation and vibration. In this study, we investigate the biomechanical properties of the microtubule under bending deformation and free vibration using 3D finite element analysis. Results of force-deformation and vibration frequencies and mode shapes obtained from the finite element analysis are presented. The results indicate that the force-deformation cha racteristics vary with time/phases and become non-linear at higher time intervals. The modes of MT vibration and frequencies are in the GHz range and higher modes will involve combined bending, torsion and axial deformations. These higher modes and shapes change their deformation which might have implications for physiological and biological behavior, especially for sensing and actuation and communication to cells. The bending force-de formation characteristics and vibration modes and frequencies should help further under stand the biomechanical properties of self-assembled microtubule .