Artificial intelligence is expected to create jobs in many industries, as well as make other jobs obsolete. One of the industries in which artificial intelligence is already important is the healthcare industry. Artificial intelligence technologies are proving that AI can perform just as well as, or perhaps even better than, human workers on certain tasks in the healthcare arena. The diagnosis of disease and finding tumors are just two areas of healthcare in which AI has already proven better than humans.
Will Artificial Intelligence Create Job Opportunities in the Healthcare Industry?
Artificial intelligence is expected to create many job opportunities in the healthcare industry, but also will eliminate many middle- and low-level jobs. On the upside, AI will help to create more new positions that will need highly trained and skilled professionals to fill them at all levels, including entry, low, middle, and management. A growing demand for artificial intelligence technologies may lead to another industrial revolution, which will demand workers who have strong technological and digital skills, along with creativity, which cannot be accomplished by AI.
AI in healthcare encompasses a range of technologies that empower machines to perceive, understand, act, and learn, enabling them to fulfill both administrative and clinical healthcare functions. As the employment landscape is undergoing rapid transformation, AI offers a solution to address the shortage of labor by easing the burden on healthcare professionals and equipping them with tools to enhance their performance. Artificial intelligence innovations are revolutionizing how medical information is gathered and transforming the dynamics of interactions with medical professionals and caregivers.
Taking all of these advancements into consideration, it’s no surprise that the healthcare industry stands to gain substantially from the growth of AI and robotics within the healthcare industry. This will, in turn, contribute to more jobs being created in the healthcare industry.
Machine Learning Applications in Healthcare
The healthcare industry uses machine learning in something that is called “precision medicine.” This involves predicting which treatments are most likely to succeed on a patient, based on the treatment context and attributes of that patient. Deep learning is already being applied to detecting clinically relevant aspects of imaging data beyond that which the human eye can see. This is helping in the early detection of cancer, tumors and other aberrations. It is even more accurate than what has been used previously, which is computer-aided detection (CAD).
Natural Language Processing Applications in Healthcare
Natural language processing is also tied to deep learning and is increasingly being used for speech recognition programs and applications in healthcare. Other NLP applications such as translation and text analysis are also important in healthcare. NLP can help to create, comprehend, and organize published research and clinical documentation. It can also be used to analyze clinical notes of providers on patients, prepare reports, conduct conversations as chatbots, and transcribe provider-patient interactions.
Use of Robots in Healthcare
Intelligent robots were approved to be used in surgery in the United States in 2000. These AI robots improve a surgeon’s ability to see and create more precise, minimally invasive incisions on patients. Surgeries that commonly use robots include prostate surgery, head and neck surgery, and gynecological surgery.
Robotic Process Automation in Healthcare
Robotic process automation involves AI performing digital tasks for administrative purposes, just as if the AI was a human following a program. In healthcare, robotic process automation, which involves the usage of computer programming, can be used to update patient records, for billing, for prior authorization, and for extracting data from images to input into other systems. In fact, image recognition is being integrated with robotic process automation to create even more intelligent and efficient AI in healthcare.
Diagnosis and Treatment Applications in Healthcare
Stanford University created MYCIN, an early rule-based system, in the 1970s to diagnose blood-borne bacterial infections. In more recent years, IBM’s Watson has been used in precision medicine, especially the diagnosis and treatment of cancer. Using machine learning and NLP, Watson was able to achieve these goals through human teaching of how to address types of cancer, but it has also presented a challenge in how to integrate Watson into care processes.
Rule-based systems such as these are being used in electronic health records systems, but are difficult to maintain as medical knowledge changes rapidly and data becomes more extensive. Research labs and technology companies are coming up with new ways to use AI in diagnosing and treatment, and they are slowly being applied to clinical practice.
Google has partnered with healthcare delivery networks to create predictive models using extensive data, aiming to alert healthcare providers about high-risk conditions like heart failure and sepsis. Another company, Enlitic, is in the process of developing AI-powered image analysis algorithms. Jvion, yet another tech company working on AI applications in healthcare, has created a “clinical success machine” designed to identify patients who are high-risk and are most likely to respond positively to treatment protocols. All of these innovations could provide healthcare professionals with invaluable decision support as they seek the most accurate diagnoses and treatment options for their patients.
Other companies, such as Flatiron Health and Foundation Medicine (both of which are owned by Roche), are specializing in providing tailored diagnostic and treatment recommendations for specific cancers based on the cancer’s genetic profile. As many cancers have a genetic component, it has become increasingly challenging for human clinicians to comprehend the myriad genetic variations associated with cancer and their responses to new drugs and treatment protocols.
AI Jobs in the Healthcare Industry
There are currently many AI-related jobs being advertised in the healthcare industry. A few of them, as of October 2023, include:
- Manager of Healthcare Analytics, Corporate, Oklahoma City, OK: $114,000 to $144,000 per year
- Software Engineering Manager for Surgical Operations, Medtronic, North Haven, CT: salary not specified
- Healthcare Systems Engineer, AI/QI Incubator, University of Florida, Gainesville, FL: $98,000 to $110,000 per year
- Artificial Intelligence/Machine Learning for Healthcare, Emory University, Atlanta, GA: $77,500 to $98,200 per year
- Scientist II, Radiology, Medical Imaging Algorithms, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD: salary not specified