How A.I. can impact the Health industry
Nowadays Artificial intelligence (A.I.) is the most attractive and lucrative topic in almost any industry. The technology works quicker, a lot more precisely and cheaper than human beings, allowing individuals to grow their skill set and invest freed up time in business growth and personal development. The impact that A.I. is expected to have within next ten to fifteen years will be extremely noticeable in healthcare industry. Responsible use of the technology should improve our quality of life, and even save our lives in various circumstances.
Here is a great example below of how recent A.I. developments can impact the industry.
Human speech is the primary source of data for psychiatrists. It helps to diagnose and treat mental disorders. Fully automated speech analysis in psychiatry can be a powerful tool for diagnostic, treatment and preventive purposes. It can give us critical information about estimated results of the treatment, and even provide some insights about possible disease risks in the future.
A.I. can impact the healthcare industry in various ways. For example HyperAspect A.I. Cloud can use images and pattern analytics capabilities in the fields of diagnostics by comparing and classifying images and identifying disturbing patterns in patients vital signs and other parameters. In the field of psychiatry NLP, it can be used to analyze the semantic coherence and syntactic complexity of the text, which are key components necessary to diagnose diseases, such as depression, generalized anxiety disorder, panic disorder, social anxiety disorder, OCD and PTSD.
Our team made quite interesting experiment in the past and wanted to share some interesting findings with you. The aim of the project was to test if we can get some clues about a potential disorder based on a diary log. The patient had to fill the log on daily basis and insert there some information about how she feels on that particular date. We used sentiment and frequency analysis to identify some severe conditions, such as sleeping disorder, depression, etc. We have evaluated sentiment score over time and monitored its trend by intersecting it with terms known to describe conditions related to the mentioned disorders. By the end of the experiment our AI Cloud helped to analyse this data and came to very surprising conclusions that helped to improve the treatment and lead to full recovery of the patient.
With the help of text analytic tools, based on A.I. and machine learning, medical specialists will have the chance to uncover diseases in early stage and start the treatment when it’s still possible to minimize the damage. By analyzing language disturbance it will be possible to predict possible development of the disease even after treatment.