Innovations in science and technology have changed the way services, and products are delivered across different sectors, and the healthcare sector is no different. In recent times, artificial intelligence (AI) has received a warm welcome in the healthcare industry. We consider how artificial intelligence has framed service delivery in the healthcare industry. We consider the current applications of artificial intelligence, the risks of the applications as well as the future of artificial intelligence in the healthcare industry.
What is artificial intelligence?
AI is a form of technology that was originally based on human intelligence. The goal was to get machines to behave with human-like intelligence. The application of AI thus involved getting machines to learn and act intelligently, as per specific commands. Therefore, artificial intelligence is associated with other forms of technology, such as machine learning.
The modern application of AI is significantly based on machine learning, which allows machines to learn independently and evolve. Machine learning algorithms allowed the machines to expand their functions as they encountered more complex data and algorithms.
Neural networks and deep learning are also behind the operations of AI. Deep learning is behind the abilities of these machines to act based on past data and trends encountered as well as infer circumstances. Neural networks are behind the coordinative functions of AI tools and act as the connection between the algorithms employed in AI.
Application of artificial intelligence in the health care sector
Even though AI is still in its infant stage in sectors such as the healthcare sector, it has applications across different aspects of healthcare. AI is applied in hospitals as well as medical research institutions as well as health insurance companies. As regards healthcare, AI is also applied in data and information management.
Disease resistance
The resistance of pathogens to established methods of disease management is notable. Pathogens have shown resistance to antibiotics, ranging from the first-line antibiotics to even the third-line antibiotics. Research has established that researchers employ AI in curbing the menace of antibiotic resistance, which has been established to cause up to 70,000 deaths around the world yearly. It is noteworthy that machine learning has seen applications in the identification of genes behind the development of antibiotic resistance. Researchers have applied machine learning in the identification of such defective genes as well as the analysis of health records to identify patterns that indicate antibiotic resistance. AI tools identify pre-symptomatic patterns that indicate the development of antibiotic resistance in a patient’s record and alert healthcare providers of these developing patterns.
Diagnostics
The unavailability of the necessary diagnostic tools has limited the management of health conditions. The limitations of diagnostic tools include the specificity of diagnostic tools as well as the untimeliness of diagnostics. AI tools have been applied to ensure proper diagnosis of diseases.
Applications of AI tools in diagnosis are linked to the fact that these tools are capable of analyzing a large volume of data and identifying trends. Thus, AI tools are adapted to identify the development of a condition from the analysis of health records as well as medical images.
AI tools have particularly promising applications as regards the diagnosis of medical conditions as they exhibit potential for providing better insight into medical conditions, providing healthcare providers with a robust diagnosis of different conditions. With the insight available from the application of AI tools, specific management strategies can also be developed.
AI systems are specially adapted to the development of specific treatment strategies because they analyze patient records as well as existing methods of treatment and research on specific conditions. As regards the development of treatment strategies, AI tools provide healthcare providers with the required resources for developing treatment strategies.
Data management
Data management is the basic area where AI tools and systems are applied. These tools include those that carry out routine data management roles. Data management is strategic to healthcare operations, as a large volume of data is routinely collected in the healthcare sector.
AI tools collect data in an efficient and timely manner, also organizing the collected data. The application of AI tools and systems for data management in the healthcare sector is known to improve the accessibility of data for subsequent processes significantly. The easy access to healthcare data driven by AI tools improves the quality of service delivery in the healthcare sector, from insurance companies to hospitals.
Brain-computer interfaces
Although these interfaces are still a limited form of form, they are built to efficiently apply in healthcare interventions such as improved communications between persons with different forms of disabilities, whether temporary or permanent, and their healthcare provider. It has been established that these AI tools can serve as a replacement for the post-stroke therapy needed to improve the communication skills of patients.
Cardiology
In cardiology, AI tools have seen several applications. These applications include the use of AI in mundane tasks, especially as regards data collection, entry, and analysis. The application of AI tools in cardiology also includes wearables for high-risk patients. These wearables include those that monitor the heart rate of high-risk patients and can initiate necessary actions. A notable application of AI in cardiology is the implantable defibrillator.
Digital consultation
It is noteworthy that AI tools are applied in digital consultation as a means of improving access to healthcare. Apps have been developed to provide digital consultation to patients based on analysis of a range of symptoms as well as the medical history of the patients.
These apps also apply speech recognition to provide medical consultations to clients based on their entries. Medical consultation based on these apps involves the recommendation of a course of action. The application of AI tools in providing digital medical consultation is aimed at improving access to medical services. There are; however, limitations to the application of these AI tools.
Drug development
The application of AI in the pharmaceutical sector includes drug development. The routine process of drug development involves lengthy and costly clinical trials which can be bypassed with the application of AI tools. These tools have been applied in the screening of available drugs for the management of diseases such as Ebola. The application of AI in the screening of drugs for curing drugs was known to discover two drugs with notable action level.
Healthcare information
Certain parts of the world still lack access to the basic information needed for maintaining health. AI tools can be applied in this regard to ensure that areas with no access to basic healthcare information can receive the required information through digital means.
Such digital means would include those that require little to no Internet accessibility provided in forms such as local languages.
Virtual Nurses
There has also been the application of AI in the provision of assistance for healthcare professionals. These platforms include virtual nurses’ platforms. The existing virtual nurse’s apps include those that provide medical assistance to patients who are recovering from conditions in between the visits of their doctors.
Virtual nurses’ platforms have also been built to provide medical assistance to persons with chronic medical conditions. The function of these apps included ascertaining whether symptoms displayed by a patient required a doctor visit. These AI tools also assisted in managing different symptoms as they presented themselves.
Apart from the existing applications of AI in the healthcare industry, there are possible applications that are billed to be in use in the upcoming years. Some of these future applications of AI in the healthcare industry include the following.
Robot-assisted Surgery
The application of AI in surgery assistance is bound to improve the outcome of surgical interventions. With these tools, the activities of surgeons will be more precise since the tools will be notably smaller and will make the tiniest incisions.
These tools could also in applied in the analysis of approaches to surgery as well as existing records to create the best approach, as per the conditions of the patient such as immune system development. The application of AI tools in surgery will especially provide surgeons as well as the rest of the surgery team to resources required for proper planning of the surgery as well as real-time resources required in the course of the surgery.
Virtual nursing assistants
There have also been indications of a more widespread application of virtual nursing assistants in the healthcare sectors. More investments in virtual nursing assistance in the near future will be inspired by the need to reduce the cost of healthcare, especially in the developed world. Research has established that an improved investment in AI tools such as virtual nursing assistants can save the US healthcare industry as much as $20 billion.
Although the healthcare industry has seen an impressive application of AI tools, the application of these tools could be associated with risks which include the following.
Improper decision making
The heavy reliance on AI tools for decision-making in the healthcare industry could lead to improper decision-making. As much as AI tools and systems are built to infer and make conclusions, these inferences are not always accurate.
Thus, a risk of the application of AI in the healthcare sector is poor decision-making, which could result from over-reliance on the tools and systems.
AI ethics
The healthcare sector is regulated by a lot of ethics. Doctors, for example, are bound by an oath to do no harm to their patients in the provision of healthcare services. Human empathy is an essential factor in the provision of healthcare services. The delivery of healthcare services is thus heavily based on the fact that humans are moral agents.
Machines, on the other hand, are mere too, without any form of morality. The involvement of AI tools, irrespective of the efficiency of these tools, poses a threat to the morality of the healthcare sector. AI tools and systems can thus lead in an unethical direction, which could contribute to negative outcomes for the patient.
Privacy
It is important to also consider the safety of the use of AI tools and systems. These tools and systems access a large volume of data which could make them easy targets for hackers. It is also noteworthy that these tools may mishandle information leading to security breaches when bad algorithms are applied. It is also noteworthy that these tools and systems could lack proper maintenance, which will jeopardize the privacy of data.
Healthcare data are particularly sensitive with available laws to ensure their privacy and security. Thus, the privacy and security of AI tools and systems, which is based on the maintenance of these tools could pose a risk.
Organizations that apply these tools thus should implement important measures to ensure the privacy and safety of personal information.
Software bias
The software that runs AI tools could also pose a threat to their use because of software bias. Software bias occurs when the software behind AI tools is not the most recent and upgraded version.
It is noteworthy that when the most suitable form of technology is not available within a setting, AI tools tend to function with subpar efficiency.
Thus, the most efficient algorithm should be applied in AI tools to prevent the associated algorithm bias.
Conclusion
There is a need for research and development towards the development of more AI tools and systems since the applicability of these tools in the healthcare sector has been established. A lot is left to be explored as regards AI in the healthcare industry. With this enhanced application also comes the enhanced need for ensuring that the use of these tools has no negative impact.
AI has been described as critical to the development of the healthcare industry in the coming times because of the peculiarities of the industry as well as the particularly efficient qualities of AI tools and systems. Improved quality of healthcare services is linked to the availability of those automated processes involved in service delivery. Generative AI Development services are thus critical to the development of the healthcare industry now and in the future.
