Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

<p>Abstract</p> <p>Background</p> <p>Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved.</p> <p>Method</p> <p>This paper introduces a new hybrid methodology <it>Expert-based Cooperative Analysis </it>(EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by <it>EbCA-Data Envelopment Analysis (EbCA-DEA)</it>, and 2) Case-mix of schizophrenia based on functional dependency using <it>Clustering Based on Rules (ClBR)</it>. In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases.</p> <p>Results</p> <p>EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here <it>Implicit Knowledg </it>-IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases.</p> <p>Discussion</p> <p>This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.</p

Towards a FPGA-controlled deep phase modulation interferometer

Deep phase modulation interferometry was proposed as a method to enhance homodyne interferometers to work over many fringes. In this scheme, a sinusoidal phase modulation is applied in one arm while the demodulation takes place as a post-processing step. In this contribution we report on the development to implement this scheme in a fiber coupled interferometer controlled by means of a FPGA, which includes a LEON3 soft-core processor. The latter acts as a CPU and executes a custom made application to communicate with a host PC. In contrast to usual FPGA-based designs, this implementation allows a real-time fine tuning of the parameters involved in the setup, from the control to the post-processing parameters.Comment: Proceedings of the X LISA Symposium, Gainesville, May 18-23, 201

Examination of Build Height in Ultrasonic Consolidation for Foil Width Specimens Using Supports

Ultrasonic consolidation (UC) is a novel, solid-state, additive manufacturing fabrication process. It consists of ultrasonic joining of thin metal foils and contour milling to directly produce functional components in a variety of geometries. The bond between layers forms when an ultrasonic horn creates a local oscillating stress field at the mating surfaces. It is commonly theorized that the high frequency vibration under pressure produces a metallurgical bond without melting the base material. The mechanism behind the bond is believed to be due to interfacial motion and friction that disrupts surface contaminants, arguably allowing direct metal to metal contact, and producing sufficient stress to induce plastic flow and promote the growth of grains across the mating surfaces. Ignored in this explanation is the role of substrate dimensions on the quality and strength of the joining process. Researchers have previously examined the effective height limitations of the build process, i.e., the limiting height to width ratio of one of the component features being fabricated. This paper extends the experimental work on using support materials to extend build height on specimens using two different candidate materials, tin bismuth, and a mixture of sugar, corn syrup, and water, referred to as “candy”. Tin bismuth and candy the represent the extremes of a tradeoff between convenience and stiffness that a support material must possess.Mechanical Engineerin

Detection of Phase Jumps of Free Core Nutation of the Earth and their Concurrence with Geomagnetic Jerks

We detected phase jumps of the Free Core Nutation (FCN) of the Earth directly from the analysis of the Very Long Baseline Interferometer (VLBI) observation of the Earth rotation for the period 1984-2003 by applying the Weighted Wavelet Z-Transform (WWZ) method and the Short-time Periodogram with the Gabor function (SPG) method. During the period, the FCN had two significant phase jumps in 1992 and 1998. These epochs coincide with the reported occurrence of geomagnetic jerks.Comment: 8 pages, 4 figure

A Preliminary Study of CO2 Flux Measurements by Lidar

A mechanistic understanding of the global carbon cycle requires quantification of terrestrial ecosystem CO2 fluxes at regional scales. In this paper, we analyze the potential of a Doppler DIAL system to make flux measurements of atmospheric CO2 using the eddy-covariance and boundary layer budget methods and present results from a ground based experiment. The goal of this study is to put CO2 flux point measurements in a mesoscale context. In June 2007, a field experiment combining a 2-m Doppler Heterodyne Differential Absorption Lidar (HDIAL) and in-situ sensors of a 447-m tall tower (WLEF) took place in Wisconsin. The HDIAL measures simultaneously: 1) CO2 mixing ratio, 2) atmosphere structure via aerosol backscatter and 3) radial velocity. We demonstrate how to synthesize these data into regional flux estimates. Lidar-inferred fluxes are compared with eddy-covariance fluxes obtained in-situ at 396m AGL from the tower. In cases where the lidar was not yet able to measure the fluxes with acceptable precision, we discuss possible modifications to improve system performance

The Respiratory Protection Effectiveness Clinical Trial (ResPECT): a cluster-randomized comparison of respirator and medical mask effectiveness against respiratory infections in healthcare personnel.

BACKGROUND: Although N95 filtering facepiece respirators and medical masks are commonly used for protection against respiratory infections in healthcare settings, more clinical evidence is needed to understand the optimal settings and exposure circumstances for healthcare personnel to use these devices. A lack of clinically germane research has led to equivocal, and occasionally conflicting, healthcare respiratory protection recommendations from public health organizations, professional societies, and experts. METHODS: The Respiratory Protection Effectiveness Clinical Trial (ResPECT) is a prospective comparison of respiratory protective equipment to be conducted at multiple U.S. study sites. Healthcare personnel who work in outpatient settings will be cluster-randomized to wear N95 respirators or medical masks for protection against infections during respiratory virus season. Outcome measures will include laboratory-confirmed viral respiratory infections, acute respiratory illness, and influenza-like illness. Participant exposures to patients, coworkers, and others with symptoms and signs of respiratory infection, both within and beyond the workplace, will be recorded in daily diaries. Adherence to study protocols will be monitored by the study team. DISCUSSION: ResPECT is designed to better understand the extent to which N95s and MMs reduce clinical illness among healthcare personnel. A fully successful study would produce clinically relevant results that help clinician-leaders make reasoned decisions about protection of healthcare personnel against occupationally acquired respiratory infections and prevention of spread within healthcare systems. TRIAL REGISTRATION: The trial is registered at clinicaltrials.gov, number NCT01249625 (11/29/2010)

Chemical laboratories 4.0: A two-stage machine learning system for predicting the arrival of samples

This paper presents a two-stage Machine Learning (ML) model to predict the arrival time of In-Process Control (IPC) samples at the quality testing laboratories of a chemical company. The model was developed using three iterations of the CRoss-Industry Standard Process for Data Mining (CRISP-DM) methodology, each focusing on a different regression approach. To reduce the ML analyst effort, an Automated Machine Learning (AutoML) was adopted during the modeling stage of CRISP-DM. The AutoML was set to select the best among six distinct state-of-the-art regression algorithms. Using recent real-world data, the three main regression approaches were compared, showing that the proposed two-stage ML model is competitive and provides interesting predictions to support the laboratory management decisions (e.g., preparation of testing instruments). In particular, the proposed method can accurately predict 70% of the examples under a tolerance of 4 time units.This work has been supported by FCT – Funda ̧c ̃ao para a Ciˆencia e Tecnologiawithin the R&D Units Project Scope: UIDB/00319/2020. The authors also wishto thank the chemical company staff involved with this project for providing thedata and also the valuable domain feedback

Scale-invariant magnetic textures in the strongly correlated oxide NdNiO3_3

Strongly correlated quantum solids are characterized by an inherently granular electronic fabric, with spatial patterns that can span multiple length scales in proximity to a critical point. Here, we used a resonant magnetic X-ray scattering nanoprobe with sub-100 nm spatial resolution to directly visualize the texture of antiferromagnetic domains in NdNiO$_3$. Surprisingly, our measurements revealed a highly textured magnetic fabric, which is shown to be robust and nonvolatile even after thermal erasure across its ordering ($T_{N\acute{e}el}$) temperature. The scale-free distribution of antiferromagnetic domains and its non-integral dimensionality point to a hitherto-unobserved magnetic fractal geometry in this system. These scale-invariant textures directly reflect the continuous nature of the magnetic transition and the proximity of this system to a critical point. The present study not only exposes the near-critical behavior in rare earth nickelates but also underscores the potential for novel X-ray scattering nanoprobes to image the multiscale signatures of criticality near a critical point.Comment: 8 pages, 3 figure

The LISA PathFinder DMU and Radiation Monitor

The LISA PathFinder DMU (Data Management Unit) flight model was formally accepted by ESA and ASD on 11 February 2010, after all hardware and software tests had been successfully completed. The diagnostics items are scheduled to be delivered by the end of 2010. In this paper we review the requirements and performance of this instrumentation, specially focusing on the Radiation Monitor and the DMU, as well as the status of their programmed use during mission operations, on which work is ongoing at the time of writing.Comment: 11 pages, 7 figures, prepared for the Proceedings of the 8th International LISA Symposium, Classical and Quantum Gravit