Products

Effective scheduling for hospital admission is a major challenge as there is uncertainty in patient’s length of stay and large errors in estimations can lead to capacity pressures. To tackle this, Virtusa-GCTS has developed a Deep Learning based solution which will accurately predict how long a newly admitted patient will stay in the hospital. The model uses cutting edge regression algorithms. This model not only helps Hospitals to plan and deploy their resources effectively but also helps insur

Customer churn refers to the loss of existing clients or customers. This solution identifies insurance customers who are more likely to close/not renew their policies with the insurance provider. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

Customer churn refers to the loss of existing clients or customers. This solution identifies E-commerce customers who are more likely to stop using the E-commerce app or the portal. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

Customer churn refers to the loss of existing clients or customers. This solution identifies newspaper customers who are more likely to discontinue their current subscription. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

Customer churn refers to the loss of existing clients or customers. This solution identifies bank customers who are more likely to close their account and leave the bank. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

This solution provides compositional analysis and predicts the number of incidents pertaining to each ticket group. The insights around incident distribution helps in proper capacity planning, resulting in efficient resource utilization.

Customer churn refers to the loss of existing clients or customers. This solution identifies broadband customers who are more likely to discontinue their current broadband service provider. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data

Customer churn refers to the loss of existing clients or customers. This solution identifies mobile network subscribers who are more likely to change their operator. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

Capillary Technologies' Customer Insights Platform, Insights+, is an AI and machine learning-powered business intelligence tool designed to transform raw data into actionable insights. It enables businesses to seamlessly aggregate data from various channels—online, in-store, and third-party sources—providing a comprehensive 360-degree view of consumers. By analyzing past and present events, Insights+ facilitates accurate forecasting and decision-making, allowing organizations to deliver prescrip

autone is an AI-driven inventory management platform purpose-built for retail and fashion brands. The platform empowers retail and consumer goods companies with precise predictions on supply and demand, helping them grow, save money, eliminate waste, and free up time to focus on their business.

Machine Learning Platform For AI provides end-to-end machine learning services, including data processing, feature engineering, model training, model prediction, and model evaluation. Machine Learning Platform For AI combines all of these services to make AI more accessible than ever.

The AMI Disease State Predictor is a machine learning model designed to predict the likelihood of Acute Myocardial Infarction (AMI, commonly known as a heart attack. By analyzing patient data, this tool aims to assist healthcare professionals in identifying individuals at risk, enabling timely intervention and personalized treatment plans. Key Features and Functionality: - Predictive Analytics: Utilizes advanced machine learning algorithms to assess patient data and predict the probability of

The Asthma Disease State Predictor is a cloud-based predictive modeling system designed to enhance the early detection and management of asthma. By leveraging advanced machine learning algorithms and real-time data analysis, this tool aims to predict asthma exacerbations, thereby improving patient outcomes and reducing emergency interventions. Key Features and Functionality: - Predictive Modeling: Utilizes machine learning techniques to analyze patient data and predict potential asthma exacerb

The Hypertension Disease State Predictor is an advanced machine learning model designed to assess the likelihood of hypertension in individuals by analyzing various medical attributes. Developed using the XGBoost algorithm and deployed on AWS SageMaker, this tool offers healthcare professionals a robust solution for early detection and management of high blood pressure. Key Features and Functionality: - End-to-End Machine Learning Pipeline: The model encompasses the entire process from data co

The Colorectal Cancer Disease Predictor is an advanced tool designed to assess an individual's risk of developing colorectal cancer. By analyzing various factors such as age, family history, lifestyle habits, and medical history, this predictor provides a personalized risk assessment, enabling early detection and proactive management strategies. Key Features and Functionality: - Comprehensive Risk Evaluation: Utilizes a wide range of data points, including demographic information, personal and

The AFIB Disease State Predictor is a sophisticated machine learning model designed to identify and predict the presence of atrial fibrillation (AFIB, the most common type of treated heart arrhythmia. By analyzing patient data, this tool aids healthcare professionals in early detection and intervention, potentially reducing the risk of complications associated with AFIB. Key Features and Functionality: - Advanced Machine Learning Algorithms: Utilizes state-of-the-art machine learning technique

The Anemia Disease State Predictor is an advanced analytical tool designed to assist healthcare providers in identifying and managing anemia within patient populations. By leveraging comprehensive data analysis, this tool enables early detection of anemia, facilitating timely interventions and improved patient outcomes. Key Features and Functionality: - Comprehensive Data Integration: Aggregates and analyzes diverse patient data to identify patterns indicative of anemia. - Predictive Analytic

The COPD Disease State Predictor is an advanced machine learning model designed to predict the risk of severe chronic obstructive pulmonary disease (COPD exacerbations. By analyzing patient data, it identifies individuals at high risk for hospitalizations related to acute COPD exacerbations, enabling timely interventions and personalized care plans. Key Features and Functionality: - Risk Prediction: Utilizes machine learning algorithms to assess the likelihood of severe COPD exacerbations, fac

The Leukemia Disease State Predictor is an advanced machine learning model designed to assist healthcare professionals in accurately diagnosing and classifying various subtypes of leukemia. By analyzing comprehensive genomic data, this tool enhances the precision and efficiency of leukemia diagnosis, facilitating timely and personalized treatment plans. Key Features and Functionality: - Multi-Class Classification: Utilizes sophisticated algorithms to differentiate between multiple leukemia sub