The Future of AI in Healthcare: How AI Technology Will Transform the Way We Heal

35 min read

July 5, 2023

How AI is Transforming the Future of Healthcare
Author
Shashank Kothari
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The world we live in today has seen tremendous advancements in technology. Different innovations are reshaping industries, and the healthcare sector stands on the precipice of a groundbreaking transformation. The future of AI in healthcare is poised to revolutionize how we deliver and experience medical care.

Imagine a future where intelligent systems work hand in hand with healthcare providers, helping them to make more accurate diagnoses, personalized treatment plans, and improved patient outcomes. The potential impact on the healthcare industry is immense, from AI-assisted diagnostics to data-driven decision support.

Fei-Fei Li, Co-Director of Stanford Institute for Human-Centered AI, once said about the healthcare future with AI, "The future of AI in healthcare is incredibly promising. With AI's assistance, medical professionals can focus on what truly matters - providing compassionate care to patients." Fei-Fei Li's perspective on the role of AI in the future of healthcare highlights its incredible promise. By using AI's assistance, medical professionals can dedicate more attention to what truly matters – providing compassionate care to patients, revolutionizing healthcare delivery for the better.

The future holds great promise in the healthcare industry, and is on the cusp of a remarkable journey. This is why embracing AI's potential to redefine how we heal and care for patients is and will be very important.

What AI in Healthcare Is All About?

Artificial intelligence is transforming healthcare. Healthcare providers are using the technology to improve patient and medical care. At its core, AI involves the development of smart systems capable of simulating human intelligence and performing tasks that typically require human cognition.

In healthcare, AI has the potential to revolutionize many aspects of patient care. By taking advantage of the power of AI, healthcare professionals can use machine learning algorithms to analyze a significant number of data and extract valuable insights. This enables more accurate diagnoses and personalized treatment plans.

The future of AI in healthcare holds immense promise. As research and advancements in AI continue, we are witnessing the unveiling of a healthcare landscape where intelligent systems collaborate with healthcare providers. This collaboration allows efficient decision-making, assists in complex procedures, and enhances healthcare delivery.

The impact of AI on the future of healthcare is multifaceted. AI-powered systems can analyze patient data, such as medical records, genetic information, and real-time sensor data, to provide valuable insights for personalized care. AI algorithms can assist in early disease detection, predict patient outcomes, and recommend treatment options based on a wealth of data.

The steps taken in using AI techniques to detect Alzheimer’s disease
Alzheimer’s disease detection using AI. Source: Link.springer.com

Many studies support the potential of AI in healthcare. For example, in a study published by Springer Link on the use of AI algorithms in the diagnosis of Alzheimer's disease, the results showed that AI algorithms have demonstrated high accuracy in detecting certain medical conditions. The study found that the AI-based approach achieved an accuracy of 90% in diagnosing Alzheimer's disease using electronic medical record data. This highlights the potential of AI algorithms to provide precise and reliable diagnostic outcomes in detecting specific medical conditions.

AI That Is Currently Making Impacts in the Healthcare Sector

AI has a wide range of influence in healthcare today, revolutionizing many processes and tasks. Here are some key areas where AI is making a significant impact.

1. Machine Learning

Machine learning is a statistical technique used with algorithms to enable computers to learn from data and make predictions or decisions without being explicitly programmed. Neural networks and deep learning are specific types of machine learning. Neural networks are computational models inspired by the human brain's structure and function, while deep learning refers to neural networks with multiple layers of interconnected nodes.

2. Natural Language Processing (NLP)

NLP focuses on understanding and processing human language. In healthcare, NLP is used for tasks such as analyzing clinical documentation, transcribing patient interactions, and creating conversational AI. NLP systems can extract insights from unstructured clinical notes and facilitate language-based interactions.

3. Rule-based Expert Systems

Rule-based expert systems use "if-then" rules to support clinical decisions. While they have been widely used in healthcare, they are gradually replaced by data-driven approaches like machine learning.

4. Physical Robots

Physical robots are used in healthcare settings, performing tasks like lifting, repositioning, and delivering hospital supplies. Surgical robots, equipped with advanced capabilities like precise incisions and stitching, assist surgeons during procedures, enhancing their abilities.

Many hospitals are making use of physical robots to perform specific tasks. Mayo Clinic in Rochester, Minnesota, for instance, is one of the leading hospitals in the world employing surgical robots. The clinic utilizes the da Vinci Surgical System to perform many procedures, including prostate cancer surgery, gynecological surgery, and minimally invasive cardiac surgery.

A robotic courier at Jena on its way to deliver essential supplies to patients
A robotic courier at Jena on its way to deliver essential supplies to patients. Source: Britannica.com

Similarly, Jena University Hospital in Germany employs a fleet of robotic couriers to transport food and essential supplies to patients, streamlining logistics and enhancing overall patient care. These robotic solutions improve operational efficiency and contribute to a smoother healthcare environment. 

5. Robotic Process Automation (RPA)

RPA is used for structured digital tasks in administrative processes. It is used for repetitive tasks like prior authorization, patient record updates, and billing. RPA can extract data from faxed images and input it into transactional systems when combined with image recognition.

Current Applications of AI in Healthcare Today

AI technologies are already revolutionizing healthcare with current applications. This paves the way for a brighter, more efficient future. AI is currently being used in the following areas:

1. Diagnosis and Treatment

AI has been employed for diagnosing and treating diseases since the 1970s. In the early 70s, MYCIN, an AI software, assisted healthcare givers in the identification of blood infection therapies. AI has since shown promise in areas like cancer diagnosis and precision medicine. However, integration issues (like data privacy, security, and regulatory compliance) with clinical workflows and electronic health record (EHR) systems have challenged widespread implementation.

Images showing the Enlitic AI tool detecting cancerous cells in the brain
Enlitic AI tool showing cancerous cells in the brain. Source: Marubeni.com

Currently, AI is being applied for the diagnosis and treatment of different sicknesses. Enlitic, for example, is a company that uses AI to develop cancer diagnosis and treatment tools. Enlitic AI tools have been shown to be able to identify cancer cells with greater accuracy than human pathologists. Enlitic's tools are also being used to develop new cancer treatments. This goes to show how AI is currently being applied in the industry.

2. Patient Engagement and Adherence

AI is used to improve patient engagement and adherence to treatment plans. Machine learning and business rules engines help personalize and contextualize care, delivering targeted interventions and tailored recommendations to patients and providers. Efforts are focused on designing effective "choice architecture" to influence patient behavior positively.

3. Administrative Applications

AI, particularly RPA, offers significant efficiencies in administrative tasks. It can be used for claims processing, clinical documentation, revenue cycle management, and medical records management. Chatbots powered by NLP are used for patient interaction and telehealth services, although concerns regarding privacy and usability remain.

The Role and Future Scope of AI in Healthcare

The future trends of AI in healthcare are vast and promising. AI has the potential to revolutionize the way healthcare is delivered, making it more efficient, effective, and personalized.

Graph showing the result of healthcare industry professionals' opinions on technologies to invest in
Healthcare industry professionals' opinions on technologies to invest in. Source: GlobalData

According to a survey conducted by GlobalData in December 2022, 50% of healthcare industry professionals plan to prioritize investing in artificial intelligence over the next two years. AI, big data, and digital media emerged as the top priorities for investment in emerging technologies. Increased trust in AI is attributed to successful use cases like AI-designed drugs entering clinical trials.

Elton Kwok, Market Research Manager in Pharma at GlobalData, highlights the potential of AI in various areas of the pharmaceutical industry, including drug discovery and data analysis, emphasizing its ability to save time and reduce costs. Kwok also said that AI's usage has yet to reach its peak and will continue to attract interest for future investment.

Below are some ways that AI is expected to impact healthcare in the future:

1. Predictive Tools and Personalized Medicine

AI will be used to track basic health data and predict illnesses even before it occurs. It will analyze even larger datasets of patient data to identify patterns and trends that can be used to personalize treatment plans.

Muhammad Mamdani talks about the future of AI in healthcare
Muhammad Mamdani talks about the future of AI in healthcare. Source: The University of Toronto

The University of Toronto, for example, has established an AI research center, the Temerty Centre for Artificial Intelligence Research and Education in Medicine. The center is making use of cutting-edge technological innovations to create a healthier future. They aim to create an app that will monitor people's health data and predict illnesses. Technologies like this and many others will help to improve patient outcomes and reduce the risk of adverse events. 

2. Disease Prevention

AI can be used to analyze data to identify patients who are at risk for certain diseases. This information can then be used to develop preventive measures or to intervene early in the disease process.

A study published by the National Center for Biotechnology Information found that AI was able to identify skin cancer with 95% accuracy, which is better than the accuracy of human dermatologists. This study suggests that AI will be able to screen for skin cancer in large populations, which could help prevent deaths from skin cancer. This shows how effective AI could be in disease prevention in the near future.

3. Drug Discovery

AI can be used to screen large libraries of compounds to identify potential new drugs or to improve existing drugs. This can help to accelerate the drug discovery process and to bring new treatments to market faster.

Atomwise, an AI-powered drug discovery company, for instance, is using AI to screen drug candidates for effectiveness and safety. The company's platform, Atomwise Virtual Screening, uses machine learning to simulate the behavior of molecules in silico. This allows Atomwise to screen millions of potential drug candidates in a fraction of the time it would take to do this in the lab. Atomwise has identified several promising drug candidates for Alzheimer's and cancer.

According to Morgan Stanley, an investment banking company, even modest improvements in early-stage drug development success rates through AI and machine learning could lead to 50 new therapies over a decade, amounting to a $50 billion opportunity. This shows that AI-enabled drug has a lucrative opportunity, with the potential for significant advancements in therapy development.

4. Clinical Decision Support

AI can be used to develop clinical decision support tools to help doctors make better decisions about patient care. These tools can analyze patient data and identify potential risks or problems.

The future of clinical decision support with AI holds the potential to improve workflows, reduce healthcare inequities, automate administrative tasks, and enhance patient care. Collaboration and careful design are crucial to ensure AI tools mitigate disparities and maximize their impact on the care delivery process.

5. Robotics

The use of AI-powered robots can only get better. AdventHealth University predicts a future in healthcare where advancements in robotics will revolutionize patient care. Robots are expected to perform lab tests, remove plaque from arteries, conduct tissue biopsies, and even target cancerous tumors. 

Additionally, robots could deliver precise medication, offer patient care for minor concerns, and engage in conversations with patients regarding their symptoms. This will help to improve patient care and reduce costs.

6. Telehealth

AI can improve telehealth services by providing a real-time interpretation of medical images and automating administrative tasks. This can make telehealth more accessible and affordable for patients.

Dr. Eric Topol, Director of the Scripps Research Translational Institute, said, while talking with Insight about how telehealth will still be useful post-pandemic: "Telehealth is here to stay, and AI will be a key part of its future. AI can help to improve the efficiency and effectiveness of telehealth, and it can also help to make telehealth more accessible to people who live in rural areas or who have difficulty traveling to see a doctor." This means that AI will continue to make the telehealth subsector even better.

Human Collaboration with AI

Using Human Expertise Alongside AI

In the rapidly evolving healthcare sector, the collaboration between humans and AI is gaining momentum. The integration of AI technologies alongside human expertise has the potential even to revolutionize healthcare delivery more and improve patient outcomes. Combining the unique capabilities of humans and AI, healthcare providers can use the strengths of each to create a more efficient and effective system.

AI systems excel in processing vast amounts of data, detecting patterns, and making predictions. However, they lack the empathy, intuition, and contextual understanding human healthcare providers possess. By using the power of AI and integrating it with human expertise, healthcare professionals can unlock new possibilities and deliver customized care at scale.

Empowering Healthcare Providers With AI

AI has the potential to empower healthcare providers by augmenting their capabilities and supporting them in many aspects of patient care. One significant area where AI can make a difference, as mentioned above, is clinical decision support. AI algorithms can analyze medical records, lab results, and imaging data to provide healthcare providers with valuable insights and recommendations for diagnosis and treatment. This can enhance the accuracy and efficiency of decision-making, leading to improved patient outcomes.

AI can also assist healthcare providers in monitoring and managing chronic conditions. By continuously analyzing patient data, AI systems can detect subtle changes and alert healthcare providers to potential issues before they escalate. This proactive approach enables timely interventions and personalized treatment plans, ultimately improving patient care and reducing hospital readmissions.

Customizing Care at Scale Through AI

One of the most promising aspects of AI in healthcare is its potential to deliver personalized care at scale. AI algorithms can analyze large datasets, including genomic information, medical histories, and lifestyle factors, to generate tailored treatment plans for individual patients. This level of personalization considers each patient's unique characteristics, optimizing the efficacy of interventions and minimizing adverse effects.

Moreover, AI-enabled tools can enhance patient engagement and education. Chatbots and virtual assistants powered by AI can provide patients with information, answer common questions, and offer guidance on self-care. This improves patient satisfaction and helps alleviate the burden on healthcare providers by addressing routine inquiries and allowing them to focus on more complex cases.

Ethical Considerations and Challenges of the Future of AI in Healthcare

Ethical and legal considerations in the future of AI in healthcare
Ethical and legal considerations in the future of AI in healthcare. Source: Frontiers

While AI holds tremendous potential in the healthcare sector, it also raises ethical considerations and challenges. Privacy and data security are critical concerns when integrating AI into healthcare systems. Safeguarding patient information and ensuring regulatory compliance is paramount to maintaining trust in the healthcare ecosystem.

Moreover, transparency and explainability of AI algorithms are essential. Healthcare providers and patients should clearly understand how AI systems arrive at their recommendations or decisions. This promotes accountability and facilitates trust between humans and AI.

Also, there is a need for ongoing training and upskilling of healthcare professionals to collaborate with AI technologies effectively. Education programs and continuous professional development can equip healthcare providers with the necessary skills to go about the evolving healthcare landscape and make the most of AI-enabled tools.

Looking Ahead

AI in healthcare represents a paradigm shift in how we deliver and experience healthcare. By taking advantage of the strengths of both humans and AI, we can achieve personalized care at scale, improve clinical decision-making, and enhance patient outcomes. 

However, it is crucial to address ethical considerations, ensure transparency, and provide appropriate training to maximize the potential of this collaboration. As we go about the future, the synergy between human expertise and AI technologies will shape a more efficient, accessible, and patient-centric healthcare ecosystem.

Conclusion 

In the ever-evolving landscape of healthcare, the crucial role of AI is becoming increasingly evident. We unlock a world of possibilities as we embrace the journey towards a future where AI is seamlessly integrated into healthcare systems. 

AI has the potential to revolutionize diagnostics, treatment, drug discovery, and patient care, providing personalized and efficient solutions. However, this journey must be approached with caution and careful consideration. Ethical considerations, privacy concerns, and the need for human oversight must guide the development and implementation of AI in healthcare. 

By taking advantage of the transformative power of AI while maintaining human collaboration, we can shape a future where healthcare is advanced and accessible and ultimately improves the lives of people worldwide.

Author
Shashank Kothari
F4P Contributor

My goal is to empower readers with insightful blogs that explore future trends, provide practical guidance, and spark curiosity. Together, let's navigate the path to personal and professional growth in an ever-changing world.

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