DXcharts
In just a few days, you can integrate and customize a lightning-fast financial table with your product. You can make changes or create a completely new interface. You want more? We offer a full access alternative. Data feeds with futures and indices, equities, FX and cryptocurrencies by default. Sign up now to get your data feeds. DXcharts can be integrated with any market data source, as it is data feed-agnostic. Native libraries for all platforms. Native web, native mobile & desktop. Get a solution that is specifically tailored to your product. Analyzing statistics from trading activity can help you evaluate securities and predict their future movements. You can create custom studies with the intuitive dxScript. You can adjust the layout of charts however you like and sync them by instrument, chart type and timeframe, range, studies & appearance.
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SurveyJS
SurveyJS is a set of four open-source JavaScript libraries that offer the benefits of a tailor-made in-house survey application, while considerably reducing the time and resources needed to deploy the system. These libraries are independent of specific server code or database requirements and seamlessly integrate with popular JavaScript frameworks, including React, Angular, Vue.js, jQuery, Knockout, and more. They are designed to communicate with any server that can handle JSON requests, ensuring compatibility with various server architectures and databases.
The product family is composed of:
- An open-source MIT-licensed rendering library that renders dynamic JSON-based forms in your web application, and collects responses.
- A self-hosted drag & drop form builder that features an integrated CSS-based theme editor and a GUI for conditional rules. It automatically generates JSON definitions (schemas) of your forms in real time.
- PDF Generator, a library that renders SurveyJS surveys and forms as PDF files in a browser;
- The Dashboard library that allows you to simplify survey data analysis with interactive and customizable charts and tables.
Visit our website to try out and evaluate our full-scale demo for free.
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Sahha
An API platform designed for health data aggregation and intelligence offers a single REST API to access wellness scores, over 50 biomarkers, and behavioral analytics sourced from smartphones and wearable devices, eliminating the need for direct device integration. The platform provides real-time webhook delivery, extensive SDK support for iOS, Android, React Native, and Flutter, all while maintaining GDPR compliance, which simplifies the process by removing the necessity for custom device integrations and machine learning model creation.
Key features include a unified REST API for health data, real-time webhook events, integration with major platform APIs like Apple HealthKit and Google Health Connect, and support for cross-platform SDKs, along with advanced behavioral intelligence processing. Developers benefit from five pre-configured wellness scores—covering Wellbeing, Activity, Sleep, Mental Wellbeing, and Readiness—over 50 raw biomarker data points, insights into behavioral archetypes and pattern recognition, as well as trend analysis and anomaly detection, complemented by 30 days of data retention with the option for unlimited access upon request.
This platform is thoroughly supported by research, ensuring its credibility and effectiveness in enhancing health insights.
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EnsoData
We are confident that Waveform AI has the potential to significantly enhance the healthcare landscape, and we are developing a platform designed to equip clinicians with essential information and support throughout the entire care continuum. Transforming healthcare truly requires collective effort, and to play our part in advancing the industry, we are publishing peer-reviewed research on AI to illustrate its benefits at every stage of the patient care experience. Our platform aims to assist providers in identifying individuals at high risk for sleep apnea by leveraging data from electronic medical records, waveforms, wearables, and various other sources, facilitating timely referrals for diagnosis. By utilizing this data, we can aid healthcare providers in pinpointing the most critical patients among the vast undiagnosed population, categorizing them based on their risk for adverse outcomes and potential healthcare costs. Additionally, we strive to streamline the diagnostic process for clinicians, enabling them to treat more patients efficiently and effectively by improving the overall quality and speed of sleep apnea diagnoses. In doing so, we hope to foster a healthier future for all patients.
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