Artificial Intelligence (AI)-Empowered Echocardiography Interpretation: A State-of-the-Art Review.

Echocardiography (Echo), a widely available, noninvasive, and portable bedside imaging tool, is the most frequently used imaging modality in assessing cardiac anatomy and function in clinical practice. On the other hand, its operator dependability introduces variability in image acquisition, measurements, and interpretation. To reduce these variabilities, there is an increasing demand for an operator- and interpreter-independent Echo system empowered with artificial intelligence (AI), which has been incorporated into diverse areas of clinical medicine. Recent advances in AI applications in computer vision have enabled us to identify conceptual and complex imaging features with the self-learning ability of AI models and efficient parallel computing power. This has resulted in vast opportunities such as providing AI models that are robust to variations with generalizability for instantaneous image quality control, aiding in the acquisition of optimal images and diagnosis of complex diseases, and improving the clinical workflow of cardiac ultrasound. In this review, we provide a state-of-the art overview of AI-empowered Echo applications in cardiology and future trends for AI-powered Echo technology that standardize measurements, aid physicians in diagnosing cardiac diseases, optimize Echo workflow in clinics, and ultimately, reduce healthcare costs.

Remediation of Perfluorooctylsulfonate Contamination by in Situ Sequestration: Direct Monitoring of PFOS Binding to Polyquaternium Polymers.

In situ methods for the sequestration of perfluorooctyl-1-sulfonate (PFOS) that are based on PFOS binding to polyquaternium polymers were reported previously, providing an approach to immobilize and concentrate PFOS in situ. To apply these methods in real life, the concentrations of polymers that permit efficient sequestration must be determined. This is only possible if the stoichiometry and strength of PFOS binding to polyquaternium polymers are known. Here, we report on the use of fluorous-phase ion-selective electrodes (ISEs) to determine the equilibrium constants characterizing binding of PFOS to poly(dimethylamine-co-epichlorohydrin) and poly(diallyldimethylammonium) in simulated groundwater and in soil suspensions. We introduce a new method to interpret potentiometric data for surfactant binding to the charged repeat unit of these polyions by combining a 1:1 binding model with the ISE response model. This allows for straightforward prediction and fitting of experimental potentiometric data in one step. Data fit the binding model for poly(diallyldimethylammonium) and poly(dimethylamine-co-epichlorohydrin) chloride in soil-free conditions and in the presence of soil from Tinker Air Force Base. When the total PFOS concentration in a soil system is known, knowledge of these PFOS binding characteristics permits quantitative prediction of the mobile (free) and polymer-bound fractions of PFOS as a function of the concentrations of the polyquaternium polymer. Because the technique reported here is based on the selective in situ determination of the free ionic surfactant, we expect it to be similarly useful for determining the sequestration of a variety of other ionic pollutants.