ARTIFICIAL INTELLIGENCE IN MEDICAL FIELD

AI brings fundamental changes in medicine

Artificial intelligence (AI) deployment in healthcare proves to be a game-changer for the challenging environment of medical industry as health AI apps demonstrate great capabilities in managing communications between doctors and patients, delivering reliable and accurate diagnosis, reducing the risk of complications as well as percentage of patients’ readmission, and drug discovery, to name a few.

While searching for ways of making diagnoses precise and fast, IBM was one of the pioneers that introduced AI for medical needs by offering clinicians Watson system to help oncologists in selecting the optimal treatment plans based on individual patient data.

In addition, the use of artificial intelligence in healthcare facilitates the market growth by creating new business opportunities for healthcare service providers. In particular, studies show that implementing clinical health artificial intelligence applications can save up to $150 billion yearly for the U.S. healthcare economy by 2026.

APPLICATION OF ARTIFICIAL INTELLIGENCE IN HEALTHCARE

Artificial Intelligence use cases in healthcare cover various areas due to the powerful ability of algorithms to bring the breakthrough practical solutions to lots of medical fields.

Diagnostics
Artificial intelligence supplies healthcare providers with mechanisms of more accurate estimations of clinical attributes, which means that clinicians get the material for generating new approaches to shaping hypotheses as well as conducting standard diagnostic processes more effectively.

For example, sophisticated health AI apps are currently used to analyze the DNA data for forecasting probable diseases. Currently, artificial intelligence in healthcare is also used for medical imaging analysis and collecting data within patient medical records. In particular, it transformed the procedure of MRI scans analysis and made it a considerably less complex process.

Robot-assisted surgery
Robotic surgeries become a wide-spread phenomenon. Overall, in the US, 693,000 robotic-assisted procedures were performed in 2017. With AI-based tools, surgeons can make more precise incisions, which in the long run greatly benefits both doctors and patients by reducing risks of complications.

Moreover, surgeons employ AI for data processing in real-time during operations. One such surgical robot is the Da Vinci: this surgical system allows medical professionals to implement complex procedures with higher flexibility while performing surgeries.

Precision medicine
Artificial intelligence operating on algorithms when combined with analysis of genomes brings revolutionary results in terms of developing the precision medicine addressing the medical needs of the individual patient.

Virtual nursing assistants
Since the need for medical assistance has been growing, the development of AI-based virtual nursing assistants has been on the rise too.

Automation of Processes
Healthcare practitioners have to consume too much time while performing routine tasks instead of focusing on interaction with patients. The AI software can facilitate the administrative routine and manage repetitive tasks including staff training, billing, processing enrollments, and tracking the medical staff work hours.

Treatment plan design
The input data is a great source for deep and insightful clinical analysis that is crucial at the stage of planning the treatment.

Therefore, AI healthcare solutions can assist medical experts in realizing the individual approach to creating treatment plans tailored to the condition of a patient.

Clinical trials
Applying artificial intelligence proves to be an optimal way of accelerating the data delivery to facilitate the clinical trial process. AI-based models significantly facilitate trial design due to application of AI-based tools for patient recruitment. As a result, with usage of AI-based monitoring systems, the considerable decrease of dropout rates can be observed.

Drug development and discovery
The drug development industry is greatly challenged by research cost and price of development costs in addition to issues pertaining to excessive time utilization.

The cost of clinical trials for drugs before approving their manufacturing can reach up to $2.6 billion with uncertain prospect of successful results. These hurdles made lots of pharmaceutical companies turn to applying such robot researchers for bringing more accurate results within the drug discovery.

Read the full article here