Most Promising AI applications in Healthcare

Most Promising AI applications in Healthcare

Artificial intelligence’s (AI) transformative power is reverberating across many industries, but in healthcare, its impact is truly life-changing. From AI-based diagnostics to robotic surgery systems, artificial intelligence software, especially Machine Learning, are increasingly used in the healthcare industry to facilitate the various stages of research and development, as well as for the treatment of patients. Their uses include the development of new drugs, diagnosis, managing diseases, and post-market analysis.

With immense power to unleash the improvements in cost, quality, and access, AI is exploding in popularity. Growth in the AI health market is expected to reach $6.6 billion by 2021—that’s a compound annual growth rate of 40 percent. In just the next five years, the health AI market will grow more than 10x2. The impact of these investments will likely be realized first in the operational and administrative side of the healthcare system rather than the clinical side, according to experts. That fits with the likely evolution of AI in other industries, too, according to PwC, which analyzed more than 300 AI use cases and found “the majority of AI’s economic impact will come from the consumption side, through higher-quality, more personalized, and more data-driven products and services.”

Here are some of the areas where AI is already starting to transform healthcare and others where experts expect it to revolutionize the sector in the coming years: 

Care Management

AI can potentially be used for planning and resource allocation in health and social services. It is also used to improve the patient experience. Alder Hey Children's Hospital in Liverpool is collaborating with IBM Watson to create a "cognitive hospital," an application that facilitates patient interactions. The application aims to identify the patient's anxieties prior to the visit and to provide clinicians with information that will help them select the appropriate treatments.

Medical Research

Artificial intelligence can analyze and identify different models faster and more accurately, especially when it comes to huge databases. It can also help researchers in their search for relevant studies and scientific literature on drug development and combine different types of data. CanSAR Cancer Research Institute database, combines genetic and clinical data of patients with information from scientific research, and uses AI to identify new anti-cancer drugs. The researchers developed Eve, an AI "science robot" designed to make the drug discovery process faster and more economical. 


AI solutions are being developed to automate image analysis and diagnosis. This helps in reducing errors during scanning to drive efficiency and reduce human error. There is also an opportunity for fully automated solutions to automatically read and interpret a scan without human oversight- which could enable instant interpretation in under-served geographies or after hours. Recent demonstrations of improved tumor detection on MRIs and CTs are illustrating the progress towards new opportunities for cancer prevention. Meanwhile, a company in ISA has already received FDA clearance for an AI-powered platform.

Surgical robot

In orthopedic surgery, an AI-assisted robotic technique can analyze data from preoperative medical records to guide the surgeon's instrumentation in real time during the procedure. It can also use data from actual surgical experience and inform the doctor about new procedures, technology. A study of 379 orthopaedic patients at nine surgical sites found that AI-assisted robotics created by Mazor Robotics reduced surgical complications by a factor of five compared to surgeons alone. In orthopedic surgery, AI-assisted robotic surgery can reduce complications and mishandling, resulting in a 21% reduction in postoperative hospital stays, and the use of AI-assisted robots can generate $40 billion in annual savings.

Virtual Care

AI virtual care has great potential for caring for patients. For example, Sensely's "Molly", currently used by the University of California, San Francisco (UCSF) and the NHS in the United Kingdom, is an AI-driven nurse avatar that interacts with patients. Ask them about their health, assess their symptoms and guide them to the most effective care environment. The study estimates that virtual care supported by AI can save $20 billion a year, saving nurses 20% of the time spent on patient care tasks.

Workflow optimization

AI can help the healthcare industry solve expensive back-office problems and productivity. The average time for nurses to work (51%) and nearly one-fifth (16%) for doctors' work are spent on activities that are not related to patient care. I-based technologies, such as speech-to-text transcription, writing icon notes, filling out prescriptions, and ordering reagents, can optimize management workflows and avoid unnecessary activities that are not related to medical care. The study estimates that this application can save $18 billion.

Final thought

In the very complex world of healthcare, AI tools can support human providers to provide faster service, diagnose issues and analyze data to identify trends or genetic information that would predispose someone to a particular disease. When saving minutes can mean saving lives, AI and machine learning can be transformative not only for healthcare but for every single patient.

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