For Wellness & Healthcare
CausalAI Accelerates Wellness Innovation
Causal Inference Platform
1 month free trialABOUT
In this era, not only lifestyles and ways of life, but also risks such as pandemics are diversifying. We at VELDT believe that the various lifelogs that are produced every day hide great hints for changing the lives of individuals with different interests and goals. We will innovate how to utilize the data produced in the real world. We will pursue the following three themes: "Realization of personalized wellness" that is close to one person, "Preventive shift from cure to care" this increases the time that can be active in health and leads to efficiency of medical resources, and lastly "Supporting healthcare innovation from various industries" this is needed because of the care-centered era. VELDT is a data science company that creates a positive spiral in each person's life and future society.
Realize personalized
wellness
Preventive shift
from cure to care
Supporting healthcare
innovation in various industries
Concept
Accelerating Wellness & Health Care Innovations
xCausal for Wellness & Healthcare is a Causal AI platform that accelerates innovation by combining lifelog data from smartphones, IoT devices, and other devices with data from medical examinations and other social activities.xCausal for Wellness & Healthcare is a Causal AI platform that accelerates innovation by combining lifelog data from smartphones, IoT devices, and other social activities with data from medical examinations and other sources.
xCausal use cases
Precision・
Nutrition
Online
Medical Services
R&D DX before
Clinical Trials
Advanced insurance
product development
For Wellness & Healthcare
Smart spaces
optimized for health
Inclusive
Smart Cities
Data-driven
health management
Best Personalized
Conditioning
The Innovation Issue:
just having data is not enough
In our survey of 200 people working for companies that are implementing or planning businesses in wellness and healthcare, approximately 90% answered that they have problems in setting ideas and themes. Of these, 60% recognize that they have data at hand but have not fully utilized it, and about 50% recognize that they rely on their personal experience and intuition.
Two Different Worlds of Health Data
Our data as patients and subjects are obtained for evidence purposes for medical treatment, testing, and research. While this data is highly reliable and accurate which is used in medicine and research, they are acquired infrequently, such as several times a year. Companies also accumulate data in specific areas that can be used in the health field. On the other hand, we in our daily lives produce life logs every day through wearables and apps. This data is often missing and varies in accuracy, but it can be obtained in time series or high frequency. Currently, due to differences in the accuracy, nature and handling of data, there is a chasm in utilizing these two types of data at the same time.
Discover and virtually validate potential healthcare needs from data
Intermittent and highly reliable data available in the medical and research fields along with daily life log data, which are less reliable but have hints of what happened during that time, are a good complement to each other if the shortcomings are compensated for. By organizing and structuring data, exploring its mechanisms and causal relationships, VELDT provides a mechanism to assist companies and institutions in finding solutions to new problems in virtual verification of hypotheses. We believe that the ability to conduct a virtual validation process prior to conducting a clinical trial or experiment will lead to a more effective experimental design and results.
Our two approaches
Our Smallytics™ technology organizes the lifelog of users, which tends to be fragmented with many missing pieces, to help users manage their physical condition. It displays the symptoms of ailments and factors that may be related to the improvement of physical condition. xCausal is a platform that links these organized data with the data possessed by companies or institutions and utilizes it for innovation.
Service Outline
xCausal is a Web service for companies
and medical institutions used in conjunction with the app
xCausal uses you'd™, a conditioning AI app that makes physical condition discoveries by utilizing smartphone lifelogs. In addition, Smallytics™ is a powered algorithmic engine that links data from the user at a company or medical institution. The user's data that is within companies and medical institutions can be linked and used with permission. The data is anonymized and statistically processed before being used through VELDT's cloud-based dashboards and causal inference engine.
※ It is also possible to use your data alone without linking to the application.
you'd™ or
Smallytics™ Onboard Apps
Data Linkage, Visualization,
Causal Inference
Service overview and process flow
"Health Data Plug-in" service for general corporate customers
To use xCausal, you must first register your company on the web. If you wish to link your lifelogs with the app, you will need to obtain a personal code from the web and distribute it to your company's users. When using the app, the target user enters the assigned personal code into the app and will need to consent to the data linkage. Consent can be given on the app screen after downloading our personal conditioning AI app you'd™ (also available as a white label). You will upload your own data from the web and link it with your personal code (no personal information is required). After the data is linked, you can use the xCausal service in an anonymized and statistical form. It is also possible to upload your own data in csv format for use without linking to the application. The data that can be used via the app is the health data in the user's iOS™ Health Care on the user's smartphone or in Google Fit when the Android™ version is released. In addition, data on physical condition, symptoms, and habits entered by the user in "you'd™". The number of users will be limited to a small number. Items with a small number of users will be displayed when we have enough people and data to display them.
"Medical Assist" service for physicians and medical institutions
The "Medical Assist" service is mainly intended for online health consultation and online medical care, and is available upon confirmation of the physician's credentials at the time of Web application. The process flow and data linkage is the same, but when obtaining consent, the user (patient) is asked to agree to disclose his/her health data and physical condition/illness symptoms on an individual basis. You can check the health data of the user by searching by his/her personal ID.
Infering causal structures and causal effects from data
The Causal Inference Option service allows you to infer causal structures from your data. The inferred structure can be modified as needed. In addition, a hypothetical "What-If ? (What-If ?)" changes can be made to simulate causal effects. The following is a simple example. "If I could double my daily steps, how would my blood pressure change?" It is possible to get an immediate prediction for such a question. As in the case below, after removing the influence from common causes (confounders) that affect both steps and blood pressure, the direct effect from steps on blood pressure can also be calculated to see the distribution of values before and after a hypothetical intervention. More advanced validation is available in the advanced version.
e.g. “how would sleep efficiency change if we could double our daily exercise?”
Virtually verify the effect of intervention
Quick modeling to assist discovery from data
Estimating the structure of a causal graph from a large number of data items requires a long computational process due to the increase in the number of combinations. In xCausal, Smallytics™ is an algorithm developed in-house that calculates and recommends data combinations that are highly relevant in consideration of causality. By using the recommendations to narrow down the number of items, a causal graph can be generated immediately. Because items can be replaced and interventions can be made immediately, trials of causal effects can be repeated quickly, leading to discoveries that have never been made before.
About Linked Apps
Collaborative apps used by users
you'd™
you'd™ is an app that utilizes your daily activity and lifelog data stored in your smartphone to provide useful discoveries for managing your physical condition. The app automatically calculates and displays what is likely to affect you by inputting your own physical condition, symptoms when you are unwell, and habits that you are implementing to manage your physical condition.
you'd™ can be white-labeled and custom-made. You can incorporate it into your own service by changing the UI design, logo, etc., and customizing branding and functions.
Smallytics™ OEM (SDK provided) and
white label instructions
It is possible to use our health day for smartphones and analysis algorithm Smallytics™ as an SDK for existing apps. Smallytics™ has a structure that cooperates with VELDT's mother AI, and we plan to send parameters learned from anonymized data accumulated in the cloud to Smallytics™ for reinforcement. This provides a mechanism for continuously improving intelligence.
Service Menu
Consists of two basic services and
a causal inference option service
xCausal consists of two basic services with different usage patterns for general enterprises and physicians / medical institutions, and an optional causal inference service. The service for physicians and medical institutions provides access to the health data of individual users (or patients), subject to confirmation of medical qualifications.
Differences in causal inference options
(for general companies)
- 5 accounts (Includes Administrator)
- Personal codes provided for user linkage
- Healthcare dashboard
- Upload your own data
- User statistics data from you'd apps available (Individual Quotation)
(for physicians and medical institutions)
- 5 accounts (Includes Administrator)
- Personal codes provided for user linkage
- Healthcare dashboard
- User physical condition dashboard (Individual)
- In-house data upload linkage
Basic Version
- Node recommendations by Smallytics
- Causal inference functionality
- Used by discretization (discrete values only)
Advanced Version
- Node recommendations by Smallytics
- Causal inference functionality
- Mixed use of discrete and continuous values
- Natural Direct Effect (NDE) Natural Indirect Effect (NIE)
- Robustness evaluation
- Article search function
- Estimates for 1,000 users/100+ items
- Use of you'd app data presets
- Use of purchased third-party data
- Use in industries other than wellness
- Custom Analytical Environments
- Analysis by our data scientists
- Project use with dedicated AI environment
- Custom use of you'd apps (white label)
- Provision of Smallytics™ SDK to your apps
- Integration into your company's services
- Integration partnerships for B2B