Cognizant and other service organizations has been in the forefront of many large scale implementations. Ex-CEO Frank Dsouza whom our CEO had a short conversation with . The question posed was - What kind of AI does he see the next generation of tech enablers create ? Learnroll approach of a Human Centric Contxual AI model which is essentially augmentation of assistive tools in healthcare scenarios. Generative AI with Open AI needs to be validated with time as a productive and safe technology to augment in various applications.With AI being the next disruption after metaverse, blockchain and more, time will tell what will be the real value to the world. AI solutions can help in assisting from generative, adaptive to predictive models.

Virtual training using web or enhanced form like VR was mostly procedural procedures using "puppet" like virtual manikins and physical mainikins.

Learnroll has received its national MBE (Minority Business Enterprise) Certification this November 2022 and our founder attended a 2 day training to understand the supplier diversity process .and benefits of the certification. The certification has been received from the NYNJMSDC council for women and minority owned businesses. We are also proud to state that most of our current website and most of our product technology development and design are also made in the US and has been implemented  by our in-house team of local developers in NJ and other contractors or services in US.

Best wishes for a great 2023 ahead! from the LEATNROLL TEAM

In the world today healthcare challenges are many and the effective way to reduce high cost of healthcare, is not just focus on subsidizing treatment or automate systems.Our goals are towards a goal using practical technology to enable solutions that impact training outcomes for healthcare that empower patients or clinicians to improve patient care especially women. However it is not a "one size fits all" solution as every woman with different demographics may have entirely different needs. In the world today healthcare challenges are many and the effective way to reduce high cost of healthcare, is not just focus on subsidizing treatment or automate systems but educate patient population on understanding the complex healthcare processes including understanding their own health as well as providing the right education and training to assist in decision making capability. On of the key reason that immersive technologies have found way to medical or health education is due to its efficacy on higher productivity with shorter trainings using various sensory cues which include visual and auditory cues. Solutions for women need higher level of analysis or empathy for developing or ensuring that the patient is provided reliable care with essential tools that help in assisting in better decision process. AI and ML can aid in this process to provide "the vision" that help in bridging the gap between education and care implementation in real life. Most women are also not self aware of their own condition and may delay care of condition. Some of the key problems women healthcare suffers from are - Investment in women healthcare research and innovation is estimated to be only 1% of a 196 B market - Source McKinsey - Just 4% of all healthcare Research and Development and just 5% of digital health investment is focused on women’s health, and women are still under-represented in nearly all clinical trials -Current investment is mostly on oncology and some chronic conditions that lead to highest woman mortality like cardiac diseases, sexual health or pregnancy/maternal health conditions is only limited to treatment solutions versus prevention or finding core root problems of gaps in care. Some of the recent reported research and news report also find a higher bias for women patients based on gender/race for ER . In summary here are some key issues - Lack of investment in woman based condition and education or training for providing higher awareness - Women have general less awareness of their own conditions - Higher rate of bias in emergency rooms delaying care - Women not having access to care or treatment and have faced more misdiagnosis than men due to lack of clinical trials of women and understanding specific "women" conditions. Our first healthcare module was for education of heart health - a major cause of mortality in US and globally. Our focus is to work towards a balanced approach and delivery modules that aid women patients to help in better care of their own health without complex terms and terminologies with aid of innovative and practical means to deliver learning that can help in making informed decisions and also result in lower healthcare costs. Most emergency cases can be considerably reduced if women or girls can understand the self care pathways for chronic conditions using tools like Classimmerse ML that help in guided training objectives.