Pega to AWS Migration

2 reviews

With over 100 Pega implementations and migrations, Virtusa has built a stronger 'Pega Migration and Modernization to AWS' competency. The competency center has built tools tailored to help clients specifically to modernize the older version of Pega and migrate to AWS cloud.

Virtusa Corporation

2 reviews

Virtusa Corporation is an IT Consulting, Technology Implementation and Application Outsourcing

ACCELLO BYOL

1 review

Accello RPA is a comprehensive RPA tool with a set of features that makes it easy to use, cost effective, scalable and more reliable as compared to traditional IT solutions

vLife

0 reviews

vLife® is Virtusa's proprietary healthcare and life sciences marketplace designed for data scientists and organizations handling extensive healthcare data. This self-service portal offers payers, providers, biopharmaceutical companies, and medical device manufacturers access to industry-specific solutions built on comprehensive journey maps. These solutions encompass pre-trained machine learning models, code snippets, tools, and accelerators tailored to the unique needs of the healthcare and life sciences sectors. Key Features and Functionality: - Pre-Trained ML Models: Access a repository of nearly 1,000 AI artifacts, enabling the development of customized ML models aligned with organizational priorities and budgets. - Synthetic Data Generation: Utilize vNet, a solution within vLife®, to generate high-fidelity synthetic tabular and image data, facilitating ML model training even when real-world data is scarce. - No-Code/Low-Code Platforms: Employ intuitive platforms like Computer Vision and Faster AI to build, train, deploy, and optimize ML models without extensive coding, enhancing efficiency and reducing operational costs. - Comprehensive Service Line Offerings: Explore solutions categorized into specific service lines, including Biopharma , Payer Services , MedTech , and Provider Services . Primary Value and Problem Solved: vLife® addresses the challenge of integrating and leveraging vast amounts of healthcare data by providing a unified platform equipped with AI and ML tools. By offering pre-built models and synthetic data generation capabilities, it accelerates the development and deployment of AI-driven solutions, leading to improved patient outcomes and operational efficiencies. The platform's no-code/low-code interfaces democratize AI adoption, enabling organizations to implement advanced analytics without requiring extensive technical expertise. Ultimately, vLife® empowers healthcare and life sciences entities to harness the full potential of their data, driving innovation and personalized care delivery.

Heart Disease - Classifier

0 reviews

The Heart Disease Classifier is a machine learning model designed to predict the likelihood of heart disease in individuals based on various health parameters. Utilizing advanced algorithms, this classifier analyzes patient data to provide accurate assessments, aiding healthcare professionals in early diagnosis and intervention. Key Features and Functionality: - Machine Learning Model: Employs sophisticated algorithms to analyze patient data and predict heart disease risk. - Data Analysis: Processes multiple health indicators, including age, blood pressure, cholesterol levels, and more, to assess risk factors. - Predictive Accuracy: Achieves high accuracy in identifying potential heart disease cases, enhancing diagnostic confidence. - Integration Capabilities: Can be integrated with existing healthcare systems for seamless data input and result interpretation. Primary Value and Problem Solved: The Heart Disease Classifier addresses the critical need for early detection of heart disease, a leading cause of mortality worldwide. By providing reliable predictions based on patient data, it empowers healthcare providers to initiate timely interventions, potentially reducing the incidence of severe cardiac events and improving patient outcomes.

Adverse Drug Reactions - Identifier

0 reviews

The Adverse Drug Reactions - Identifier is an advanced AI-driven solution designed to automate the detection, extraction, validation, and reporting of adverse drug reactions (ADRs from scientific literature. By integrating multiple specialized agents, this framework streamlines pharmacovigilance processes, ensuring timely and accurate regulatory submissions while enhancing patient safety. Key Features and Functionality: - Automated Literature Screening: Continuously scans scientific journals, regulatory bulletins, and clinical trial publications to identify relevant safety information. - Intelligent Data Extraction: Utilizes natural language processing (NLP and machine learning to accurately extract adverse event data, including drug-event relationships and patient demographics. - Validation and Knowledge Integration: Cross-references extracted data with existing safety databases and regulatory guidelines to validate findings and reduce false positives. - Regulatory Report Generation: Automatically converts validated adverse event information into standardized regulatory submission formats, such as Individual Case Safety Reports (ICSR. - Orchestration and Workflow Management: Coordinates the activities of all specialized agents, managing the workflow from literature search to report submission. Primary Value and User Benefits: This solution addresses the challenges of managing the increasing volume and complexity of drug safety data. By automating labor-intensive processes, it enhances efficiency and scalability in pharmacovigilance workflows. Users benefit from improved signal detection capabilities, ensuring early identification of potential safety issues. Additionally, the system ensures compliance with global regulatory standards, facilitating accurate and timely submissions to health authorities. Overall, it supports better patient outcomes through proactive risk management and streamlined reporting processes.

Patient Eligibility for Cancer Trials

0 reviews

The "Patient Eligibility for Cancer Trials" solution, available on AWS Marketplace, is designed to streamline the process of matching cancer patients with appropriate clinical trials. By leveraging advanced artificial intelligence and machine learning technologies, this solution automates the pre-screening process, significantly reducing the time and effort required by clinicians to identify suitable trials for their patients. Key Features and Functionality: - Automated Pre-Screening: Utilizes AI to analyze patient medical records and match them against clinical trial eligibility criteria, enhancing efficiency and accuracy. - Integration with Clinical Trial Databases: Connects seamlessly with existing clinical trial registries to access up-to-date information on available trials. - Customizable Matching Parameters: Allows for the adjustment of matching criteria to align with specific patient needs and trial requirements. - User-Friendly Interface: Provides an intuitive dashboard for clinicians to review and manage potential trial matches. Primary Value and Problem Solved: This solution addresses the challenges clinicians face in identifying and enrolling patients in suitable cancer clinical trials. By automating the pre-screening process, it reduces the time required to match patients with trials by approximately 40%, as demonstrated in real-life clinical trial matching tasks. This efficiency not only accelerates patient access to potentially life-saving treatments but also enhances the overall effectiveness of clinical research by facilitating the enrollment of eligible participants.

Type2Diabetes - Identifier

0 reviews

The vLife Type2Diabetes Identifier is a specialized tool designed to assist healthcare professionals in the early detection and management of Type 2 Diabetes. By analyzing patient data, it identifies individuals at risk, enabling timely intervention and personalized care plans. Key Features and Functionality: - Risk Assessment: Utilizes advanced algorithms to evaluate patient information and determine the likelihood of developing Type 2 Diabetes. - Data Integration: Seamlessly integrates with existing electronic health records (EHR systems for comprehensive analysis. - User-Friendly Interface: Provides intuitive dashboards and reports for easy interpretation of results. - Customizable Alerts: Offers configurable notifications to inform healthcare providers of high-risk patients. Primary Value and Problem Solved: The vLife Type2Diabetes Identifier addresses the critical need for early detection of Type 2 Diabetes, a condition that often remains undiagnosed until complications arise. By identifying at-risk individuals promptly, it empowers healthcare providers to implement preventive measures, reducing the incidence of diabetes-related complications and improving patient outcomes.

CogniSense

0 reviews

CogniSense is an innovative middleware IoT platform designed to help enterprises initiate and accelerate their Internet of Things (IoT journey. Built with a microservices-based, plug-and-play architecture, it offers a flexible and scalable solution for integrating IoT devices and managing data. CogniSense provides a comprehensive suite of services, including data analytics, processing, and visualization capabilities, enabling businesses to derive actionable insights from their IoT ecosystems. Key Features and Functionality: - Edge Computing with Simple Event Processing: Facilitates real-time data processing at the edge, reducing latency and enhancing responsiveness. - Adaptive Device Provisioning (ADP: Supports automatic bulk provisioning of devices, streamlining the onboarding process and ensuring efficient device management. - Scalable and Modular Services: Allows enterprises to utilize the full suite of CogniSense features or selectively implement services based on specific needs, ensuring flexibility and scalability. Primary Value and Problem Solved: CogniSense addresses the challenges enterprises face in deploying and managing IoT solutions by providing a robust, scalable, and user-friendly platform. Its microservices architecture and plug-and-play model simplify the integration of diverse IoT devices, while its advanced analytics and visualization tools transform raw data into meaningful insights. By leveraging CogniSense, businesses can enhance operational efficiency, make informed decisions, and drive innovation in their IoT initiatives.