A comparative analysis of deep learning-based location-adaptive threshold method software against other commercially available software.

Automatic segmentation of the coronary artery using coronary computed tomography angiography (CCTA) images can facilitate several analyses related to coronary artery disease (CAD). Accurate segmentation of the lumen or plaque region is one of the most important factors. This study aimed to analyze the performance of the coronary artery segmentation of a software platform with a deep learning-based location-adaptive threshold method (DL-LATM) against commercially available software platforms using CCTA. The dataset from intravascular ultrasound (IVUS) of 26 vessel segments from 19 patients was used as the gold standard to evaluate the performance of each software platform. Statistical analyses (Pearson correlation coefficient [PCC], intraclass correlation coefficient [ICC], and Bland-Altman plot) were conducted for the lumen or plaque parameters by comparing the dataset of each software platform with IVUS. The software platform with DL-LATM showed the bias closest to zero for detecting lumen volume (mean difference = -9.1 mm3, 95% confidence interval [CI] = -18.6 to 0.4 mm3) or area (mean difference = -0.72 mm2, 95% CI = -0.80 to -0.64 mm2) with the highest PCC and ICC. Moreover, lumen or plaque area in the stenotic region was analyzed. The software platform with DL-LATM showed the bias closest to zero for detecting lumen (mean difference = -0.07 mm2, 95% CI = -0.16 to 0.02 mm2) or plaque area (mean difference = 1.70 mm2, 95% CI = 1.37 to 2.03 mm2) in the stenotic region with significantly higher correlation coefficient than other commercially available software platforms (p < 0.001). The result shows that the software platform with DL-LATM has the potential to serve as an aiding system for CAD evaluation.

Automated Web-based Software for CT Quality Control Testing of Low-contrast Detectability using Model Observers.

The Channelized Hotelling observer (CHO) is well correlated with human observer performance in many CT detection/classification tasks but has not been widely adopted in routine CT quality control and performance evaluation, mainly because of the lack of an easily available, efficient, and validated software tool. We developed a highly automated solution - CT image quality evaluation and Protocol Optimization (CTPro), a web-based software platform that includes CHO and other traditional image quality assessment tools such as modulation transfer function and noise power spectrum. This tool can allow easy access to the CHO for both the research and clinical community and enable efficient, accurate image quality evaluation without the need of installing additional software. Its application was demonstrated by comparing the low-contrast detectability on a clinical photon-counting-detector (PCD)-CT with a traditional energy-integrating-detector (EID)-CT, which showed UHR-T3D had 6.2% higher d' than EID-CT with IR (p = 0.047) and 4.1% lower d' without IR (p = 0.122).

Mixed Reality as a Digital Visualisation Solution for the Head and Neck Tumour Board: Application Creation and Implementation Study.

The preparation and implementation of interdisciplinary oncological case reviews are time-consuming and complex. The variety of clinical and radiological information must be presented in a clear and comprehensible manner. Only if all relevant patient-specific information is demonstrated in a short time frame can well-founded treatment decisions be made on this basis. Mixed reality (MR) technology as a multimodal interactive user interface could enhance understanding in multidisciplinary collaboration by visualising radiological or clinical data. The aim of the work was to develop an MR-based software prototype for a head and neck tumour board (HNTB) to support clinical decision-making. The article describes the development phases and workflows in the planning and creation of a MR-based software prototype that were required to meet the multidisciplinary characteristics of a HNTB.

Single-Subject TMS Pulse Visualization on MRI-Based Brain Model: A precise method for mapping TMS pulses on cortical surface.

Highly accurate visualization of the points of transcranial magnetic stimulation (TMS) application on the brain cortical surface could provide anatomy-specific analysis of TMS effects. TMS is widely used to activate cortical areas with high spatial resolution, and neuronavigation enables site-specific TMS of particular gyrus sites. Precise control of TMS application points is crucial in determining the stimulation effects. Here, we propose a method that gives an opportunity to visualize and analyze the stimulated cortical sites by processing multi-parameter data.•This method uses MRI data to create a participant's brain model for visualization. The MRI data is segmented to obtain a raw 3D model, which is further optimized in 3D modeling software.•A Python script running in Blender uses the TMS coil's orientation data and participant's brain 3D model to define and mark the cortical sites affected by the particular TMS pulse.•The Python script can be easily customized to visualize TMS points task-specifically.

A scoping review of virtual care in the health system: infrastructures, barriers, and facilitators.

For virtual care models to be able to improve the safety and quality of care, it is essential to identify the strengths and weaknesses of virtual care. In this Scoping review, literature published on virtual care was identified using international databases. The results of the included studies were summarized using a predefined taxonomy. In total, 20 studies were included in the present review. Extracting the findings of the articles showed four main topics, including "virtual care delivery models," "Video conference software platforms to provide virtual care," "virtual care delivery challenges," and "virtual care implementation facilitators." Therefore, with the development of emerging digital technologies, unique opportunities to provide virtual care and improve the provision of health services have been created in the health care system worldwide. Multifunctional video conference software platforms using specific models for each scope of care practice should be considered.

Automated systematic evaluation of cryo-EM specimens with SmartScope.

Finding the conditions to stabilize a macromolecular target for imaging remains the most critical barrier to determining its structure by cryo-electron microscopy (cryo-EM). While automation has significantly increased the speed of data collection, specimens are still screened manually, a laborious and subjective task that often determines the success of a project. Here, we present SmartScope, the first framework to streamline, standardize, and automate specimen evaluation in cryo-EM. SmartScope employs deep-learning-based object detection to identify and classify features suitable for imaging, allowing it to perform thorough specimen screening in a fully automated manner. A web interface provides remote control over the automated operation of the microscope in real time and access to images and annotation tools. Manual annotations can be used to re-train the feature recognition models, leading to improvements in performance. Our automated tool for systematic evaluation of specimens streamlines structure determination and lowers the barrier of adoption for cryo-EM.

Electronic Method (Pro-Kin) for Improving And Speeding up The Recovery after Ankle Sprain.

BACKGROUND AND OBJECTIVE: Ankle sprains, very common injuries occurred especially during sports activities, are mainly caused by indirect trauma, which influences exaggerated stress exceeding the strength of stabilization mechanisms. Up to 85% of such injuries result from a sudden flexion and inversion of the foot. In this study, we analyzed the effectiveness of the platform Pro-kin, an innovative system that has given us the possibility to combine the functionality of the older proprioceptive boards with very accurate software in order to improve and accelerate the recovery after ankle injuries. METHODS: 30 patients with moderate ankle sprain outcomes in two groups (A and B) were included in this study. Group A was only treated with proprioceptive exercises for 3 weeks, while the group B was trained with the innovative Pro-kin. In both groups, we evaluated VAS scale, the ratio between the number of circumductions performed by the injured foot and the time spent on doing them and the percentage of load among the injured and the healthy foot in statics and dynamics with electronic baropodometry. Our data has been collected at t0 (beginning of study), t1(one week later), t2 (two weeks later), t3 (one month later), t4 (two months later), and then analyzed by the two-way analysis of variance (2-way ANOVA) test. RESULTS: At t0 no statistical differences of pain in the 2 groups (3.3 and 3.4); the values were similar, as well as at time t1, t2, t3 and t4. Therefore we deduce that Pro-kin treatment is not painful. The number of circumductions performed was definitely better in B group since the first week; for the A group the values considerably increased only at t3 (one month later). Comparing the load percentages on two feet detected by the electronic baropodometer in statics and in dynamics, we deduced that the patients of A group tend to lean mostly on the healthy foot than B group. CONCLUSIONS: This study demonstrates that new technological resources (such as Pro-kin) may be helpful to improve and speed up the recovery of ankle sprain in athletes.

[Design and Implementation of Software Platform for AI-ECG Algorithm Research].

A software platform for AI-ECG algorithm research is designed and implemented to better serve the research of ECG artificial intelligence classification algorithm and to solve the problem of subjects data information management. Matlab R2019b and MySQL Sever 8.0 are used to design the software platform. The software platform is divided into three modules including data management module, data receiving module and data processing module. The software platform can be used to query and set the subjects information. It has realized the functions of data receiving, signal processing and the display, analysis and storage of ECG data. The software platform is easy to operate and meets the basic needs of scientific research. It is of great significance to the research of AI-ECG algorithm.

SIGVerse: A Cloud-Based VR Platform for Research on Multimodal Human-Robot Interaction.

Research on Human-Robot Interaction (HRI) requires the substantial consideration of an experimental design, as well as a significant amount of time to practice the subject experiment. Recent technology in virtual reality (VR) can potentially address these time and effort challenges. The significant advantages of VR systems for HRI are: 1) cost reduction, as experimental facilities are not required in a real environment; 2) provision of the same environmental and embodied interaction conditions to test subjects; 3) visualization of arbitrary information and situations that cannot occur in reality, such as playback of past experiences, and 4) ease of access to an immersive and natural interface for robot/avatar teleoperations. Although VR tools with their features have been applied and developed in previous HRI research, all-encompassing tools or frameworks remain unavailable. In particular, the benefits of integration with cloud computing have not been comprehensively considered. Hence, the purpose of this study is to propose a research platform that can comprehensively provide the elements required for HRI research by integrating VR and cloud technologies. To realize a flexible and reusable system, we developed a real-time bridging mechanism between the robot operating system (ROS) and Unity. To confirm the feasibility of the system in a practical HRI scenario, we applied the proposed system to three case studies, including a robot competition named RoboCup@Home. via these case studies, we validated the system's usefulness and its potential for the development and evaluation of social intelligence via multimodal HRI.

A Web-Based Interactive Patient-Provider Software Platform Does Not Increase Patient Satisfaction or Decrease Hospital Resource Utilization in Total Knee and Hip Arthroplasty Patients in a Single Large Hospital System.

BACKGROUND: Web-based platforms used to enhance patient-provider communication are being explored to improve patient satisfaction and care delivery, and decrease cost. This study tested a web-based interactive patient-provider software platform (IPSP), JointCOACH, which enabled patient communication with their care team and preparatory/recovery guidance. The aims of this study are to compare (1) patient satisfaction and (2) healthcare resource utilization by patients who underwent total knee and hip replacements and added IPSP to standard of care (SOC). METHODS: This study is a prospective, randomized clinical trial at a single large academic healthcare system. Between May 2018 and March 2020, 399 patients undergoing elective total hip or knee arthroplasty were randomized to SOC arm (n = 204) or SOC + IPSP arm (n = 195). Patient demographics, surgical details, and comorbidities were collected. Patient satisfaction was assessed using Visual Analog Scale and the Picker Patient Experience-15. Healthcare utilization was measured using length of stay, emergency department and office visits, office calls, readmissions, and reoperations at 30 and 90 days after surgery. RESULTS: No difference was found in length of stay between SOC and SOC + IPSP. No differences were found in 30-day or 90-day satisfaction or in healthcare resource utilization (P > .05) including number of office and emergency department visits, phone calls, and readmissions. CONCLUSION: Statistical differences were not found in satisfaction and healthcare utilization with the addition of IPSP to SOC. IPSP can be used to reinforce patient education and communication between the patient and provider, and should be evaluated as an element of virtual care rather than supplementing traditional in-office follow-up. CLINICALTRIALS.GOV: More information on this study can be found at clinicaltrials.gov NCT03499028.

Design and Implementation of Software Platform for AI-ECG Algorithm Research / 中国医疗器械杂志

A software platform for AI-ECG algorithm research is designed and implemented to better serve the research of ECG artificial intelligence classification algorithm and to solve the problem of subjects data information management. Matlab R2019b and MySQL Sever 8.0 are used to design the software platform. The software platform is divided into three modules including data management module, data receiving module and data processing module. The software platform can be used to query and set the subjects information. It has realized the functions of data receiving, signal processing and the display, analysis and storage of ECG data. The software platform is easy to operate and meets the basic needs of scientific research. It is of great significance to the research of AI-ECG algorithm.

A2A: a platform for research in biomedical literature search.

BACKGROUND: Finding relevant literature is crucial for many biomedical research activities and in the practice of evidence-based medicine. Search engines such as PubMed provide a means to search and retrieve published literature, given a query. However, they are limited in how users can control the processing of queries and articles-or as we call them documents-by the search engine. To give this control to both biomedical researchers and computer scientists working in biomedical information retrieval, we introduce a public online tool for searching over biomedical literature. Our setup is guided by the NIST setup of the relevant TREC evaluation tasks in genomics, clinical decision support, and precision medicine. RESULTS: To provide benchmark results for some of the most common biomedical information retrieval strategies, such as querying MeSH subject headings with a specific weight or querying over the title of the articles only, we present our evaluations on public datasets. Our experiments report well-known information retrieval metrics such as precision at a cutoff of ranked documents. CONCLUSIONS: We introduce the A2A search and benchmarking tool which is publicly available for the researchers who want to explore different search strategies over published biomedical literature. We outline several query formulation strategies and present their evaluations with known human judgements for a large pool of topics, from genomics to precision medicine.

Development of Sensors-Based Agri-Food Traceability System Remotely Managed by A Software Platform for Optimized Farm Management.

The huge spreading of Internet of things (IoT)-oriented modern technologies is revolutionizing all fields of human activities, leading several benefits and allowing to strongly optimize classic productive processes. The agriculture field is also affected by these technological advances, resulting in better water and fertilizers' usage and so huge improvements of both quality and yield of the crops. In this manuscript, the development of an IoT-based smart traceability and farm management system is described, which calibrates the irrigations and fertigation operations as a function of crop typology, growth phase, soil and environment parameters and weather information; a suitable software architecture was developed to support the system decision-making process, also based on data collected on-field by a properly designed solar-powered wireless sensor network (WSN). The WSN nodes were realized by using the ESP8266 NodeMCU module exploiting its microcontroller functionalities and Wi-Fi connectivity. Thanks to a properly sized solar power supply system and an optimized scheduling scheme, a long node autonomy was guaranteed, as experimentally verified by its power consumption measures, thus reducing WSN maintenance. In addition, a literature analysis on the most used wireless technologies for agri-food products' traceability is reported, together with the design and testing of a Bluetooth low energy (BLE) low-cost sensor tag to be applied into the containers of agri-food products, just collected from the fields or already processed, to monitor the main parameters indicative of any failure or spoiling over time along the supply chain. A mobile application was developed for monitoring the tracking information and storing conditions of the agri-food products. Test results in real-operative scenarios demonstrate the proper operation of the BLE smart tag prototype and tracking system.

Source Data for the Focus Area Maturity Model for Software Ecosystem Governance.

We define a software ecosystem as a set of organizations collaboratively serving a market for software and services. Typically these ecosystems are underpinned by a common technology, such as an extendable software platform. This data set supports the article that describes the Software Ecosystem Governance Maturity Model ( S E G - M 2 ) [50]. The model has the goal to support software ecosystem orchestrators in the management and governance of the actors in their ecosystems in a structured way. Through a critical structured literature review, 168 practices have been collected. These practices have been evaluated through six case studies at software ecosystem orchestrators. The practices are described with a practice code, a practice name, a practice description, required success conditions, the person responsible for the practice, and the associated literature where the practice was identified.

Optimal Path Planning for Selective Waste Collection in Smart Cities.

Waste collection is one of the targets of smart cities. It is a daily task in urban areas and it entails the planning of waste truck routes, taking into account environmental, economic and social factors. In this work, an optimal path planning algorithm has been developed together with a practical software platform for smart and sustainable cities that enables computing the optimal waste collection routes, minimizing the impact, both environmental (CO2 emissions and acoustic damage) and socioeconomic (number of trucks to be used and fuel consumption). The algorithm is executed in Net2Plan, an open-source planning tool, typically used for modeling and planning communication networks. Net2Plan facilitates the introduction of the city layout input information to the algorithm, automatically importing it from geographical information system (GIS) databases using the so-called Net2Plan-GIS library, which can also include positions of smart bins. The algorithm, Net2Plan tool and its extension are open-source, available in a public repository. A practical case in the city of Cartagena (Spain) is presented, where the optimal path planning for plastic waste collection is addressed. This work contributes to the urban mobility plans of smart cities and could be extended to other smart cities scenarios with requests of optimal path planning.

Use of new interactive patient-provider software improves patient satisfaction and outcomes-a retrospective single-center study.

BACKGROUND: While a number of studies have explored patient- and provider-related factors contributing to quality of care, few studies have explored the role of technology in improving quality and optimizing patient-provider communication. This study explores the use of an interactive patient-provider software platform (IPSP) at a single institution. Specifically, we compared: (1) patient satisfaction scores, (2) complication rates, and (3) readmission rates before and after the use of an IPSP on patients undergoing total hip arthroplasty and total knee arthroplasty. MATERIAL AND METHODS: A retrospective review was performed on all total hip arthroplasty and total knee arthroplasty patients who completed a Press Ganey survey at a single institution between the years 2014 and 2017. Primary outcomes included Press Ganey patient satisfaction scores and 90-day complication and readmission rates. Mann-Whitney U testing and chi-squared analyses were conducted to assess continuous and categorical variables, respectively. RESULTS: Analysis revealed an improvement in median Clinician and Group Consumer Assessment of Healthcare Providers and Systems (89 vs 97) and Hospital for Consumer Assessment of Healthcare Providers and Systems scores (9 vs 10; P < .001) between pre-IPSP and post-IPSP. There was a decrease in 90-day complication rates (17.3 vs 11.2%; P = .035) but no decrease in readmission rates (0.30 vs 0.18%, P = .322) between the 2 time points. CONCLUSIONS: The use of an IPSP proved instrumental in improving patient satisfaction and lowering 90-day complication rates at a single institution. The implementation of an IPSP may prove beneficial to arthroplasty surgeons and health-care institutions alike seeking to optimize the quality of care. Larger multicenter studies are necessary to validate the results of the present study.

Integrative and theoretical research on the architecture of a biological system and its disorder.

An organism stems from assemblies of a variety of cells and proteins. This complex system serves as a unit, and it exhibits highly sophisticated functions in response to exogenous stimuli that change over time. The complete sequencing of the entire human genome has allowed researchers to address the enigmas of life and disease at the gene- or molecular-based level. The consequence of such studies is the rapid accumulation of a multitude of data at multiple levels, ranging from molecules to the whole body, that has necessitated the development of entirely new concepts, tools, and methodologies to analyze and integrate these data. This necessity has given birth to systems biology, an advanced theoretical and practical research framework that has totally changed the directions of not only basic life science but also medicine. During the symposium of the 95th Annual Meeting of The Physiological Society of Japan 2018, five researchers reported on their respective studies on systems biology. The topics included reactions of drugs, ion-transport architecture in an epithelial system, multi-omics in renal disease, cardiac electrophysiological systems, and a software platform for computer simulation. In this review article these authors have summarized recent achievements in the field and discuss next-generation studies on health and disease.

A New Software Platform to Improve Multidisciplinary Tumor Board Workflows and User Satisfaction: A Pilot Study.

BACKGROUND: Workflow and preparation for holding multidisciplinary cancer case reviews (i.e., Tumor Boards) is time-consuming and cumbersome. Use of a software platform might improve this process. This pilot study assessed the impact of a new software platform on tumor board preparation workflow and user satisfaction compared to current methods. MATERIALS AND METHODS: Using current methods and the NAVIFY Tumor Board Solution, this study assessed the number of tasks and time to prepare tumor board cases. Participants completed online surveys assessing ease of use and satisfaction with current and new platforms. RESULTS: A total of 41 sessions included two surgeons, two oncologists, two pathologists, and two radiologists preparing tumor board cases with 734 tasks were recorded. Overall, there was no difference in the number of tasks using either preparation method (341 current, 393 NAVIFY Tumor Board solution). There was a significant difference in overall preparation time as a function of specialty (F = 71.74, P < 0.0001), with oncologists, radiologists, and surgeons having reduced times with NAVIFY Tumor Board solution compared to the current platform and pathologists having equivalent times. There was a significant difference (F = 38.98, P < 0.0001) for times as a function of task category. Review of clinical course data and other preparation tasks decreased significantly, but pathology and radiology review did not differ significantly. The new platform received higher ratings than the current methods on all survey questions regarding the ease of use and satisfaction. CONCLUSIONS: The study supported the hypothesis that the new software platform can improve Tumor Board preparation. Further study is needed to assess the impact of this platform in different hospitals, different data storage systems, with different observers, and different types of Tumor board cases as well as its impact on the quality of the tumor board discussion.

TDat: An Efficient Platform for Processing Petabyte-Scale Whole-Brain Volumetric Images.

Three-dimensional imaging of whole mammalian brains at single-neuron resolution has generated terabyte (TB)- and even petabyte (PB)-sized datasets. Due to their size, processing these massive image datasets can be hindered by the computer hardware and software typically found in biological laboratories. To fill this gap, we have developed an efficient platform named TDat, which adopts a novel data reformatting strategy by reading cuboid data and employing parallel computing. In data reformatting, TDat is more efficient than any other software. In data accessing, we adopted parallelization to fully explore the capability for data transmission in computers. We applied TDat in large-volume data rigid registration and neuron tracing in whole-brain data with single-neuron resolution, which has never been demonstrated in other studies. We also showed its compatibility with various computing platforms, image processing software and imaging systems.

Design, Implementation and Operation of a Reading Center Platform for Clinical Studies.

Clinical reading centers provide expertise for consistent, centralized analysis of medical data gathered in a distributed context. Accordingly, appropriate software solutions are required for the involved communication and data management processes. In this work, an analysis of general requirements and essential architectural and software design considerations for reading center information systems is provided. The identified patterns have been applied to the implementation of the reading center platform which is currently operated at the Center of Ophthalmology of the University Hospital of Tübingen.