Grand Challenges at the Interface of Engineering and Medicine.

Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution is now equipped at varying degrees of sophistication with the ability to monitor human health in both non-invasive and invasive modes. The multiple scales at which human physiology can be interrogated provide a profound perspective on health and disease.

Prediction for the Risk of Multiple Chronic Conditions Among Working Population in the United States With Machine Learning Models.

Chronic diseases have become the most prevalent and costly health conditions in the healthcare industry, deteriorating the quality of life, adversely affecting the work productivity, and costing astounding medical resources. However, few studies have been conducted on the predictive analysis of multiple chronic conditions (MCC) based on the working population. Seven machine learning algorithms are used to support the decision making of healthcare practitioner on the risk of MCC.

A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks.

Here we employ and adapt the image-to-image translation concept based on conditional generative adversarial networks (cGAN) for learning a forward and an inverse solution operator of partial differential equations (PDEs). We focus on steady-state solutions of coupled hydromechanical processes in heterogeneous porous media and present the parameterization of the spatially heterogeneous coefficients, which is exceedingly difficult using standard reduced-order modeling techniques. We show that our framework provides a speed-up of at least 2,000 times compared to a finite-element solver and achieves a relative root-mean-square error (r.

Characterization of the collagen microstructural organization of human cervical tissue.

The cervix shortens and softens as its collagen microstructure remodels in preparation for birth. Altered cervical tissue collagen microstructure can contribute to a mechanically weak cervix and premature cervical dilation and delivery. To investigate the local microstructural changes associated with anatomic location and pregnancy, we used second-harmonic generation microscopy to quantify the orientation and spatial distribution of collagen throughout cervical tissue from 4 pregnant and 14 non-pregnant women.