Artificial intelligence is instrumental as one of the most effective solutions in modern-day healthcare technology. In fact, in 2021, the global market size of this innovation in the medical field was valued at $10.4 billion. Within which clinical trial applications and robot assisted surgery accounted for the largest revenue shares.
AI can be trained with the thought and decision process of medical professionals. It can sense, observe, learn, record, analyze, interpret, and act on medical data. These abilities of AI will complement human efforts and increase the success rate of medical procedures. Moreover, the advantages that AI can bring might actually enable humans to achieve precision medicine.
“Precision medicine means that we need to deliver in the context of workflow decision support to the clinician to do the right thing at the right time.”
— John Halamka
It is almost an impossible quest for humans in the medical sector to keep abreast with the increasing inflow of information about health conditions, treatments, and medical technology.
This is a good reason for the further development of artificial intelligence in this industry. The use of smart health tools is also another expansion opportunity for AI and machine learning as it helps in solving health issues.
Benefits of Artificial Intelligence in Healthcare
Let’s first take a closer look at the advantages of artificial intelligence in healthcare to determine why you should be interested in pursuing this type of development.
Higher Operational Efficiency
Healthcare organizations deal with myriads of data. From patient medical history to insurance documents, there’s no shortage of information that needs to be taken into account when running a facility.
AI can make things easier by going through large volumes of data at the fraction of the speed that humans usually require. Moreover, it can detect patterns that may be invisible to the human eye. Thus, simplifying various operational tasks and boosting overall workflow efficiencies.
Improved Patient Care
Another one of AI in healthcare benefits that you should know is the improvement of patient care. First, artificial intelligence can free up medical professionals from administrative work to focus on patients. Yet, that’s not all.
By developing a comprehensive, AI-enabled digital infrastructure, organizations can speed up and increase the accuracy of diagnostics to provide better personal medical advice. Thus, resulting in fewer errors and lower risks to patients.
Reduction in costs is the natural byproduct of higher operational efficiency within the healthcare sector. However, besides that, AI can also be used with the specific goal of lowering expenses.
Thanks to its ability to quickly analyze data, AI can spot bottlenecks and identify areas where costs can be reduced without a significant impact on operational performance. So, if you’re looking to minimize spending, consider turning to AI and automation in healthcare.
Challenges of AI in Healthcare
While artificial intelligence has proved its value in enhancing medical services, healthcare providers shouldn’t rush to adopt it without considering a few things.
Privacy and Security Measures
Privacy and security measures are still the number one priority when developing and deploying AI and ML technologies for the healthcare sector.
A bulk of sensitive patient data is generated and processed with the use of AI tools. Thus, you need a high level of protection from any breaches and other vulnerabilities in order to avoid potential losses that leaks can incur.
Another important moment to keep in mind is regulatory compliance. Within the medical sector, there are multiple guidelines to adhere to depending on where you operate. For example, HITECH and HIPAA, which aim to protect health data, particularly when there is adoption of new technologies.
Their violation entails significant penalties and risks. Thus, if you want to avoid unnecessary headaches, it’s best to turn to professionals who are experienced in developing complaint apps.
12 Use Cases of AI in Healthcare
Artificial intelligence has an influential role to play in patient care and a great potential to change the landscape of healthcare services. It has already delivered meaningful results in various sciences of medicine.
Let’s take a look at the top applicable ways that AI is impacting health-related matters:
1. Robot Assisted Surgery
As we’ve seen at the beginning of this article, robot assisted surgery is an AI application in healthcare that’s taking up a large portion of the global market.
Before you get carried away though, it’s important to reiterate that this use case is not about replacing doctors. Rather, it’s about keeping them in control but having an AI-powered robotic instrument to help carry out precise, flexible motions.
Typically, robot-assisted surgery is associated with minimally invasive procedures which are performed through minuscule incisions and result in:
- Fewer complications
- Faster recovery time
- Less pain, blood loss, and scarring
With such advantages, it’s easy to see why some hospitals are excited to leverage these types of technologies.
2. Clinical Trials Participation
When medical professionals pursue clinical research, recruitment of trial participants can be the most time-consuming and expensive part of the entire process. This is because it’s imperative to find the right group of people whose health characteristics make them eligible to qualify for each specific clinical trial.
However, as artificial intelligence becomes more used in healthcare, recruitment for trials can become much easier. With the help of data science best practices and natural language processing algorithms that scan patient health records, you can efficiently identify patients that are eligible for your study.
3. Research and Development
AI can help in the discovery of new medications based on records of prescribed drugs and medical intelligence. The use of big data and AI can assist in the investigation and discovery of new medications for specific illnesses, and the result will be a big plus for pharmaceuticals.
Comparative effectiveness of drugs and medical devices can be advanced by the use of top-notch technologies. Deep machine learning can choose the most applicable information from data records for experimental design to indicate the best medical solutions.
The root genetic cause of ailments in humans can be researched by biotech companies using AI. Gene components and analysis will be understood better. The further use of AI could help in forecasting the results of gene editing.
4. Medical Imaging and Diagnostics
Radiology spans imaging techniques, such as X-rays and treatments like radiation therapy while Radiography is restricted to performing the actual imaging tests. These tests are usually X-rays, CT scans, and MRI procedures.
Medical imaging is a great fit for AI adoption, the use of computer vision technology can help intelligent systems to observe photographs or results of scans. The application of deep learning can interpret images in detail.AI in radiology is already being used for reading images, but a doctor still needs to review the results. Click To Tweet
An example is the case of the University of Rochester Medical Center. It announced the application of AI to identify and prioritize the urgency of ill patients and schedule who sees the doctor first.
AI also helps to diagnose skin cancer more accurately than human experts with the use of skin images. This has lowered the cases of false positives in assessing symptoms, allowed to reduce the waiting list for surgery, and make sure that only real patients get treatments.
5. Digital Consultations
The availability of a very rich database and application of deep structured learning is a superior combination for digital consultation. This is because deep learning is a method based on studying data representations other than using algorithms that are task-specific. In this case, deep learning enables the system to make well-informed decisions based on millions of cases that are relevant to the case of a specific patient.
Natural language processing is also a viable option for a digital consultation in healthcare. It is able to understand complicated sentences other than the selection of predefined options.
Advanced natural language processing is simply the study of human language from a computational perspective. It covers syntactic, semantic and discourse processing models, emphasizing machine learning or corpus-based methods and algorithms. Real-time AI conversational analysis together with deep structured learning will solve the problem of answering patients’ questions and recommend the best action.
6. Personal Medical Experience
People with specific family medical histories and records can get highly detailed diagnoses and treatments. AI can consider risk factors like allergies and genetics to make treatments better. Unlike other personalized options, AI can be superior as more data collections are actualized using learning models.
Home-use AI-driven diagnosis is still in the making, but successful and interesting tests are being made. A good example is Remidio, by analyzing the photos of a patient’s eye, a mobile phone diagnosis of diabetes is possible.
With the existence of an applicable dataset in AI, personalized medication could analyze a person’s gene and chromosome to decide the best treatment, however, such a dataset must be created first.
7. Cybersecurity and Blockchain
We can’t look away from the risk of hackers as many AI solutions are functional thanks to the internet. The connectivity to the internet can make room for cyber-attacks and hospitals can’t afford to take that risk. Thus, stakeholders in the medical field are already adopting stronger cybersecurity policies.
AI can solve the problem of cybersecurity. Advanced solutions are fashioned by the use of machine learning to observe and understand unusual network behavior. It can also fish out and block abnormal or anomalous activities by indicating attacks or vulnerabilities.
The application of Blockchain in AI can help in securing health data storage and its management. The trust of blockchain and AI in data analytics will be of value in securing and permitting users to extract data. It will also make the process of data storage in hospitals transparent and secured with cryptography.
8. Healthcare Management
Medical data records can be of great use beyond average data management. Using AI, the data obtainable from health records can be used in the analysis of price and risk management of services based on competition and market conditions.
Marketing research of pharmaceuticals can be facilitated too, as well as automating everyday office and administrative operations in medical centers, especially report generation.
9. Health Predictions and Forecasts
During a coma, AI can analyze brain scans and indicate in its results the possibility of recovery and influence the withdrawal of life-support. A Chinese trial has been able to accurately predict exit from a coma where human doctors could not foresee one. AI was 90% accurate by tracking blood flow to the brain and any other details omitted by the human eye.
“It will never replace doctors. It is just a tool to help doctors and families make better decisions.”
— Dr. Song Ming
10. Clinical Decision Support
It’s hard to overestimate the role of artificial intelligence in medical diagnosis. Helping to deliver and analyze valuable data, AI supports clinical decision-making and expands treatment options.
With the use of classification and regression algorithms, this powerful technology elevates prognosis and can predict the risk of a certain disease. While there’s still a need for human intervention to make conclusions and give recommendations, it’s highly possible that soon we’ll see these tasks performed autonomously.
AI allows healthcare professionals to see patterns in the patient data and leverage them to drive better outcomes. For instance, it’s feasible now to determine the right number of days patients have to spend at the hospital, which leads to more accurate care planning and reduced readmissions.
11. Automating Administrative Tasks
Healthcare providers primarily concentrate their efforts on the delivery of patient care, the quality of medical services, and the patient experience. Yet, they also need to function as a business dealing with administrative tasks, often time-consuming and costly.
Artificial intelligence can help healthcare professionals significantly reduce time spent on daily office operations and allocate resources on what really matters.
For example, in the billing processes, AI can optimize invoice management and orchestrate the workflows between the bank, insurance, and healthcare specialists. On top of that, it’s used to control the management of the medical equipment lifecycle.
12. Wearable Health Devices
Considering the volume of health data that can be harvested in an individual’s lifetime, it’s a good idea for tech companies to look for opportunities in wearable health devices.The use of intelligent devices can give more flexibility and alternatives to usual health assessments. Click To Tweet
Some of these health assessments usually require visiting a doctor. For example, in the case of diabetes, blood pressure, Parkinson’s disease, multiple sclerosis, etc.
The use of intelligent Internet of Things medical devices can allow for data sharing with doctors. For example, the introduction of ECG/EKG wearables by Qardio, an AI health company, reveals an effective method of collecting the most needed information for diagnosis at a short interval. This technology can also help to reduce the premiums for health insurance.
Companies are now making intelligent wearable devices for runners and other forms of light sports or exercise. An example is the “smart sock” embedded with sensors. This device is readily substituting the usual hospital machinery for measuring postural ways or the likelihood of falling at a lower cost.
The general applications and possible uses of Artificial Intelligence in the healthcare industry are growing. From the complexity of robot surgeons to the use of automated chats to cure depression — there’s a lot in store for the future of artificial intelligence in healthcare.
The great union of AI and ML solutions in the healthcare industry is very promising. This is due to the large data sets and records available from over the years. ML patterns can learn to detect ailments, suggest the diagnosis, and even predict the duration from convalescence to total healing.
The health industry is a place for no risks and recklessness. Hence the implementation and use of AI must be top-notch. The purpose of using AI is to effectively save lives, therefore much effort must go into improving, perfecting, deploying, and regulating the use of such technology.