Artificial Intelligence

Chatbots

1Axium continues to advance the practical application of AI and Data Analytics in the fields of Behavioral Health and the Social Sciences. A particular focus of the company is in the area of AI enabled Cognitive behavioral therapy (CBT) Chatbots. CBT is a type of psychotherapeutic treatment that can educate people how to identify and change destructive or disturbing thought patterns that have a negative influence on behavior and emotions. These AI based chatbots run on smart mobile devices and are available 24/7/365.

According to government sources, mental health therapy is on the rise with one in five adults in the United States (17.9 percent) experiencing some type of mental health disorder; overtaking heart conditions, which was the costliest. Approximately $201 billion is spent on mental health annually. Because of the costs associated with treatment, many individuals who experience mental health problems do not receive timely professional input. Also, a contributing factor is the shortage of therapists and the stigma associated with mental illness. Chatbots have proven to be very effective intermediate surrogate until a human psychotherapist can be seen and/or afforded.

In general CBT chatbots are developed for the majority population. To be effective for ethnicities requires the chatbots to be tailored to be culturally and ethnically sensitive. 1Axium is working with a major CBT developer and psychologists to tailor these technologies to reflect the multiplicity of races and ethnicities. We are also investigating how this application can be used to address the needs of the disabled.

AI-enabled population health

AI can be leveraged to monitor and assess population health and select target public health interventions based on AI-enabled predictive analytics. This software platform includes data-driven algorithms that map the spread and burden of disease, while an AI predictive analytics algorithm is used to project future disease spread and possible future outbreaks. Medical Epidemiology (AIME) will significantly benefit from these AI-based predictive models affording practitioners a more insightful understanding of the risk across different groups.

Patient virtual health assistants

AI based Patient Vrtual Health Assistants applications are designed to give control to the patient for certain health care functions.

  • Self-referral – eliminates the primary physician
  • Deep learning algorithms can take a patient’s symptoms, vitals, health history and determine possible prognosis
  • AI-facilitated self-care functions based on medical history and prognosis.

They can also provide value and efficiency gains to the broader health system by ensuring that only patients who truly need to go to health facilities do so. Thus freeing up health providers’ time for acute patients, and by remotely collecting ongoing patient data which can be linked to a patient’s broader medical record.

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