An AI platform applied to the analysis of medical images to reduce the time-to-market of solutions supporting physicians and radiologists.
Corporate Welfare expands thanks to AI and focuses on prevention and collaboration. The Corporate Wellbeing evolves into with a data-driven logic and focuses on Artificial Intelligence, Machine Learning, and IoT to further contribute to the promotion of health, promoting a culture of prevention its employees (both inside and outside the company).
Health is the most requested benefit and an essential driver to better develop its human capital, intellectual, and business performance. Corporate Wellbeing initiatives appear like a necessary investment, particularly in the light of longer working lives, and fruitful in terms of productivity, corporate reputation, employer branding, and retention.
The global health emergency has further confirmed the crucial importance of the health issue, not just in terms of a right and health cost, but as a common good, shared responsibility, and conscious individual path, to live long and as best as possible in the interest of all.
Governmental and healthcare institutions, large companies, insurance companies and tech players - each with their own abilities - can make a valid contribution to build Health Protection processes, guarantee better living conditions and higher chances of facing critical situations with fewer impacts, as long as supported by adequate technological infrastructures.
Digital platforms play an important role, not only in the Corporate area but for the entire community: they enable a better managed, more accurate, significantly more efficient health management. They may reduce the need for contact between people (thus the risk contagion) and increase the ability to monitor epidemiological phenomena; help prevent the onset of chronic diseases; maximise stakeholders’ engagement and the promotion of a culture of prevention-oriented adoption of healthy lifestyles, through collaborative and continuous interaction models with and between users.
The solution named “Live Well - Do It Better” uses Artificial Intelligence and Machine Learning engines applied to Big Data to promote the long-term health of employees.
Live Well - Do It Better is scalable, modular and cloud-ready. Alternatively, installation on local infrastructure is possible.
It is a recommendation and coaching system that, thanks to AI and data about habits and lifestyles provided by employees, freely and in compliance with privacy (GDPR-compliant), suggests actions, advice and readings customised aimed at improving the quality of life and prevention: from stress management to nutrition to chronic diseases prevention, from which specialist medical consultations contact in the event of the onset of particular clinical phenomena, to psychological support or suggestions in the wellness field. Laife Reply declined in a perspective corporate and life-long wellbeing a tool now widely consolidated in the digital consumer markets: recommendation engines are filtering software that provides platform users with targeted information on the content of potential interest. Live Well - Do It Better is based on a data platform in which data is collected to create specific recommendations for the employee according to manifested and detected health needs, supporting him in accessing the contents most relevant to him and, through personalised interactions, towards the adoption of healthy lifestyles, improving the employee experience.
The solution, possibly integrated into company platforms, involves the construction of an employee-centric and data-driven ecosystem that develops from personal and customisable diaries (suitably protected and segregated) in which information is collected to monitor the health of the employee who has chosen to join the program. Each diary constitutes a dossier concerning a specific area such as, for example, physical activity, blood sugar levels, heart rate, pedometer, sleep monitoring, and includes analytical services based on descriptive statistics that propose trend analyses, performance indicators, and other relevant statistical information. The accuracy of the recommendation is directly proportional to the increase in data collected about and with the employee.
The platform is designed to support both batch and real-time data, system, and device integrations. The data collection is done through the Internet of Medical Thing (IoMT) devices provided by the employer, like wearables (which measure parameters such as pressure, temperature, oxygenation, etc.) and through the Health Corners. They are interactive totems installed in the company (e.g. scale, sphygmomanometer, pulse oximeter, ECG), available to employees. Further data regarding nutrition, laboratory test reports, etc. can be entered directly by the user at any time, using the Web and mobile interfaces. Another possibility is the integration of the platform with third-party systems and applications such as public health systems or healthcare services booking applications. These integrations are particularly useful if the employee has previous or chronic pathologies or in a context such as the current epidemiological emergency, to contribute to providing more information on the phenomenon in question, starting with geo-referencing
Through the platform, participants in the Live Well - Do It Better program have the opportunity to access a network of professionals formed, for example, by specialised physicians, fitness trainers, psychologists, nutritionists (and by any figure that the employer believes wants and can make available) who offer consultations and recommendations based on the information the employee chooses to share. Each professional does not have full visibility of the data, but only accesses those for which the program participant has given consent and can be preparatory to the specific area of competence. The interaction between employees and professionals is managed by the platform which, in addition to a Web interface, offers an Android and iOS mobile application.
The solution also includes a proactive and personalised Virtual coach, to support the employee in using the platform and to encourage them to keep their data updated or to carry out healthy activities. Machine learning is the basis of Virtual coach, which is not intended to substitute for the professionals but works alongside them supporting them in managing the relationship with employees, offering them a different experience from traditional paths.
Through the Virtual coach (or alternatively through the mobile and Web interfaces) it is possible to administer to users useful questionnaires in the clinical pre-screening phase or to intercept perception and satisfaction concerning a particular path. Another engagement mechanism proposed by Live Well - Do It Better is the construction of competitions (challenges) between colleagues in the context of corporate initiatives and events, using gamification techniques.
The AI & ML engines will be able to further optimise profiling, analysis, by combining information relating to personnel (data collected from wearable, IoT and IoMT devices, clinical reports, diagnostic test results, data entered manually by the employee through mobile and Web app or interacting directly with the Virtual Coach) with environmental measurements such as humidity, noise, and brightness, through IoT sensors and assess the impact of these values on the health and well-being of employees. The data is managed in streaming to allow the analytical services of the platform to infer in near real-time behaviours, alert situations, and recommend actions to be taken.
Laife Reply promotes digital innovation in the Healthcare sector, taking advantage of its extensive skills and expertise in advanced Artificial Intelligence and Big Data Analytics technologies, with in-depth know-how in the medical field. Laife Reply is specialised in the application of Artificial Intelligence algorithms to images and clinical data, with the aim of adding value to healthcare processes and contributing to the reduction of clinical risk, through real support in relation to diagnosis and treatment activities.