HOW IS ARTIFICIAL INTELLIGENCE HELPING THE HEALTH SECTOR?
Medicine is one of the fields with the most to gain from applying Artificial Intelligence. This is undeniable. Right now, AI can help doctors to improve their diagnoses and treatments although – beware! – Artificial Intelligence should never replace them. It is and will remain a great ally, meaning that AI can help solve complicated medical situations, although the ultimate decision must always come down to medical and healthcare professionals.
USE CASES WHERE ARTIFICIAL INTELLIGENCE
BENEFITS THE HEALTHCARE AND PHARMACEUTICAL SECTOR
Let’s look at some use cases of applying Artificial Intelligence to help take giant steps in such an important sector.
One example might be early detection of tumours. AI helps take the strain off radiologists, reducing their fatigue or allowing them to focus on more complex cases.
AI systems learn from large patient image banks provided by healthcare institutions that wish to make scientific progress, working with solutions specialised in Artificial Intelligence and Machine Learning such as ENAIA. Diagnoses from AI systems combined with diagnoses from specialist doctors ensure a very high level of reliability.
In addition to early detection of tumours, Artificial Intelligence can help avoid false diagnoses, a very important factor in both human and economic terms as it avoids putting patients though unnecessary tests and reduces associated costs.
MORE PERSONALISED TREATMENTS
During their lifetime, a person generates enough health data to fill millions of books. Based on this premise, scientific researchers are training AI solutions to analyse medical records and help doctors provide more personalised treatments based on scientific studies and on patient records. To do so, Artificial Intelligence technology is fed with data from books on medicine, medical journals and other specialised texts.
FASTER DRUG DEVELOPMENT
Thanks to Artificial Intelligence, it is possible to refer to infinite medical records related to a particular pathology or disease [such as patients over an entire continent] and this makes it possible to characterise and classify the ideal candidates to test a specific experimental drug. This great technological progress makes it possible to reduce the pharmaceutical industry’s manufacturing processes considerably. Furthermore, it not only saves time but also represents a considerable cost saving.
Applying AI in drug development is also a great help to diagnose the causes of any drug’s side effects. As we know, many drugs end up being withdrawn from the market after approval due to negative reactions. In this respect, Artificial Intelligence can help us decipher how components are metabolised in the organs and diagnose whether they are toxic or harmful before moving on to clinical tests or putting it on the market. This is a great step forward to improve medicines and their results, as well as representing a great cost saving for pharmaceutical companies.
Implementing Artificial Intelligence applied to Health implies major ethical challenges that must be addressed before committing to this revolutionary technological innovation. We cannot forget that AI in the healthcare and pharmaceutical sector is an assistance tool and that its results will always be checked and validated by medical and pharmaceutical specialists.
ENAIA, ARTIFICIAL INTELLIGENCE FOR THE HEALTHCARE AND PHARMACEUTICAL SECTOR
Ethical questions and lack of knowledge of the potential of new technology are some of the factors slowing down healthcare and pharmaceutical organisations and institutions on their path to digital transformation. ENAIA is determined to inform the entire sector about the great potential and revolution represented by implanting Artificial Intelligence solutions in the Health field. ENAIA’s specialisation and professionalism [as a platform specialising in Machine Learning and Artificial Intelligence] and its hard-wired solution developed by scientific researchers, make it the perfect sidekick to include new Artificial Intelligence technology.