Ehave, Inc. Uses Artificial Intelligence And Machine Learning for Big Data Management in Mental Health Care

Ehave, Inc. (OTC: EHVVF), is a provider of digital therapeutics for the psychedelic and mental health sectors, announced today plans to continue to address the needs of big data management in mental healthcare. Ehave has been using artificial intelligence and machine learning since the first version of its Ehave Dashboard to transform clinical research, identify treatment protocols, and increase the virtual care capabilities of health providers.

FREMONT, CA: Before the COVID-19 pandemic, Ehave began testing AI models for clinical and psychedelic researchers to perform predictive analysis about patient data. With COVID-19 cases still spreading rapidly as the virus mutates, many academic institutions and health systems have developed predictive technology to track the virus and simulate the risk of COVID-19 patients developing different symptoms. The Ehave Dashboard will continue to evolve to include its artificial intelligence and machine learning functions in order to become more integrated with clinical care in the coming years.

Ehave Dashboard has been in the forefront of using data analytics with its blockchain data warehouse that provides insights to clinicians and patients. The health system continuously improves upon their system by layering on new tools, such as artificial intelligence and machine learning, bringing them closer to predictive analytics. 

The digital transformation among health systems was well underway when 2020 began. The COVID-19 pandemic underscored the need for centralized and efficient data management. Ehave has sped up development of data-gathering and reporting efforts during the pandemic, as well as cloud implementations to securely store and coordinate data. The use of BurstIQ enforces strong cybersecurity in secure data storage.

“Ehave moved predictive analytics to the forefront for mental health. The acceleration and acceptance of digital technology in 2021 means more health systems now have the technical capabilities to practice precision medicine as they move closer to predictive analytics,” said Ben Kaplan, CEO of Ehave. Mr. Kaplan continued, “The Ehave dashboard has machine learning-powered models to identify high risk and the likelihood of problems among mental health patients. This offers healthcare providers more efficient patient management.”

The future of healthcare involves analytic insights being used at the bedside during the point of care. Analytics will enable healthcare professionals to proactively manage care and keep people out of the hospital and healthy. Wearables and other biomedical devices, combined with machine learning and artificial intelligence will challenge traditional healthcare organizations and data scientists to the forefront of improving patient care outcomes.