AI is transforming all industries in all corners of the world, with healthcare being one significantly impacted.
Healthcare is also one of the earliest domains that AI is being taken seriously.
AI in healthcare is improving the functioning of our medical systems, enhancing the accuracy of diagnoses, personalizing treatment programs, and enriching the healthcare experience for patients.
AI is sorting through vast amounts of relevant medical data to offer meaningful and timely information and insights to support the decision-making of healthcare providers, researchers and experts alike, ultimately helping to bring about more effective decisions about healthcare.
In this article, we focus on understanding how AI is changing diagnosis and treatment, common applications and benefits, as well as challenges in practice.
The Rise of AI in Healthcare
In the last decade, artificial intelligence (AI) has evolved from a programmatic device to a trusted solution being utilized in laboratories, clinics, and hospitals.
The healthcare delivery system generates a phenomenal amount of data in cancer clinical referenced notes, imaging data, genomic data, and demographic information on patients.
It is impossible for any human or committee of humans to think through and interpret data to that extent.
Again, which is the reason we have AI!
AI systems can comb through the data and see the trends and lend assistance to think clinically through machine learning (ML), deep learning, and natural language processing (NLP).
With the explosion in demand for telemedicine, precision medicine, and decision-making by data, the experts in the industry predict the global AI in healthcare market will be on the verge of explosive growth in the near future.
AI in Healthcare: Improving Speed and Accuracy for Diagnosis
One of the most interesting uses of AI for healthcare is related to medical diagnosis.
The evaluation of a diagnosis consists of numerous lab tests, imaging, and analysis by humans who can let things slip by, even the most experienced providers, because of fatigue or the volume of work or patients seen daily.
This is changing with AI diagnostic tools.
The machine learning algorithms that have synthesized information from hundreds to thousands of medical imaging studies can typically identify abnormalities faster than a human expert and with more accuracy.
1. Medical Imaging and Radiology
AI algorithms are now being used to interpret X-rays, MRIs, CT scans and mammograms with extraordinary precision.
AI-enabled platforms can analyze data to accurately identify cancers, fractures and conditions in the early stages of development; in some cases, before there are any visual indicators of disease.
Thus, clinical teams are able to make diagnoses more rapidly and initiate treatment earlier, which may bear a significant effect on overall mortality from diseases such as cancer.
2. Pathology and Lab Analysis
AI technologies are automating pathology processes by examining slides and tissue samples for signs of disease.
This process not only decreases the potential for human error, but it may decrease the timelines for lab results.
With imaging systems and predictive modeling combined with AI in pathology, efficiencies are vastly improved across laboratories all over the world.
3. Predictive Diagnostics
AI is bringing forward an avenue for predictive diagnoses by exploring patient data to evaluate the risk of potentially developing disease.
Examples of predictive models being utilized may determine patients at risk for diabetes, heart disease, and neurological disease, with a progressively higher degree of accuracy, long before any disease symptoms might present, driving the patient to seek preventative care and altered lifestyle.
AI in Treatment: Individualizing treatment and care
AI will change how treatment strategies are developed, implemented, and sustained.
While AI can take many forms to recommend and deliver individualized treatments, the common denominator is aggregating patient data, genetic data, and clinical literature.
1. Precision Medicine
AI is enabling a new way for precision medicine — the treatment is based on the patient’s genome, lifestyle, and the environment.
For example, AI algorithms can sift through difficult quantities of genetic data to determine how certain classes of patients might respond to a particular drug in an effort to minimize the trial-and-error process of prescribing medication.
2. Drug Discovery and Development
The typical timeframe to bring a drug to the market from idea to discovery to development to commercialization can require decades of time and multi-million dollar investments.
AI could shorten this timeframe by predicting if a class of compounds is likely to be useful against a certain disease in as short as a month.
AI considers both chemical structures as well as biological processes to shorten the timeline to accelerate drug discovery and development to bring to market treatment that will ultimately save lives.
3. Robotic Surgery
AI systems will provide robotic functions to make surgery better by providing new means and capabilities to improve precision and control in surgical procedures.
AI robotic systems would analyze and take advantage of the incoming data of the imaging devices and monitors on the patient to bring more meaning into the decision making during the surgical procedures.
These AI robotic systems would likely guide the surgeon better in less invasive surgery that
AI in Patient Care: Enriching patient and improving processes for patient outcomes
In addition to diagnostic and treatment applications, AI is improving not only the process of patient care, but the operations of a hospital/health system.
From the AI chat-bots that can understand basic queries from patients, to predictive analytics for hospital resource planning, AI technology can, will, and is being used more frequently to support an experience that is centered on the patient and efficiency of practice.
1. Virtual Health Assistants
Hospital systems and telehealth providers realize more than ever the value of using AI via virtual assistants and chatbots.
The virtual assistants can assist patients with scheduling appointments, reminding patients to take any maintenance drugs, and following up on symptoms and instructions following illnesses or procedures.
AI Health Assistants can also serve as a caretaker for patients who have chronic illnesses and can be available for assistance as well as monitoring patient symptoms, and if needed, notify the health provider for intervention.
2. Remote Monitoring and Wearables
Wearables and devices utilizing today’s AI innovations represent a truly astonishing shift in how health information is collected and assessed.
Smart watches and health monitors provide the ability to capture continuous readings of a person’s vitals that include heart rate, oxygen saturation, information related to sleep, and statistics.
AI’s ability to manage and assess vitals repeatedly over time can alert when there is an anomaly that is predictive of a health threat to a patient.
This gives time for medical providers to intervene when necessary.
3. Predictive Hospital Management
Hospitals are using AI technology to better track patient flow in real-time and allow for a better management of staffing needs, and when using this technology, predict times when health services are being utilized the most.
5 Major Benefits of AI in Healthcare
Integrating artificial intelligence technology into clinical decision making in the healthcare system provides significant advantages for and to patients, providers, and the system.
- Academic Diagnostic Accuracy: AI can significantly reduce human errors and achieve improved accuracies in also earlier differential diagnosis with fewer missed diagnostic possibilities.
- Individualized Treatment Regiment: AI makes use of algorithms to provide more tailored treatment regiments for therapy and treatment models.
- More Convenient Workflows: AI technology can improve processes and operations within hospitals.
- Cost Savings Opportunities: The organization can utilize AI to systematically determine redundant tests and assist in identifying and developing effective treatment regiments for cost savings.
- Improved Patient Experience: AI can enhance the patient experience in that patients could consistently utilize resources for support in what to do in treatment and recovery through a mobile app or AI that the patient feels comfortable doing.
AI will create data democratization and will build a better brand of human intelligence that will enable enhanced and better proactive, predictive, and patient-centric care.
Challenges and Considerations with Ethics.
It is well known that AI will revolutionise healthcare; however, much is still out there, , we should be clear about the challenges:
- Data Privacy and Security: Medical data is highly sensitive information, and any breach of medical data/records can be catastrophic. So while this may be a sticking point…we believe that protecting against potential breach through better cyber defense mechanisms and compliance with personal data and health data privacy laws is one of the most crucial rules to follow
- Algorithmic Bias: Data that are for AI can be fraught with bias or lacking so that AI models can and will produce inaccurate, even unjust results.
- Regulatory Approval: The healthcare industry is expecting validated systems/certificates that the AI systems are safe prior to the deployment of newly developed AI systems.
- Integration with Legacy Systems: Some hospitals (and systems), will need to integrate the AI function into older systems and those systems likey used outdated data systms….and likely also require a manual transcription or cut and paste of old information into a new system. Such a process may also make the task or another step potentially impossible to complete.
- Human Oversight: Lastly, while AI would provide you another tool to support decision making, the primary decision still rests with the medical providers…either the decision is made by medical providers with the support or a decision based on information provided by AI language model or another data-based, other resource, to help with decision making.
The Role of AI in the Future of Healthcare
There is tremendous excitement about a future where machines powered by AI will play an important role in healthcare applications.
The advancement of technology will continue to provide us with the opportunities to demonstrate AI in predictive analytics, genomics, mental health intervention, and real-time monitoring of chronic disease processes.
The benefit of AI will only grow in significance as we witness more clinical adoption, use applications in the Internet of Medical Things (IoMT), and distributed ledger technology applications (blockchain).
The IoMT and blockchain will be used, in part, to improve data sharing and interoperability as well as accountability as we build trust among the actors in the digital health ecosystem.
AI is not going to replace licensed providers, but it is going to augment the capabilities and competencies of licensed providers.
AI will help relieve pressures on providers by helping to automate some components of tasks at various levels of care (primary care to specialty care) as well as potentially help providers make informed decisions on the fly, empowering effective mediation and helping clinicians get back to what they do best — providing meaningful care to patients.
In short, AI will soon be and is already beginning to provide faster, smarter, and personalized innovation in healthcare. Technology enables important AI based diagnostic capabilities. Technology provides important robotic assisted surgical capabilities. Technology also has and will enable virtual health assistants.
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