Artificial intelligence (AI) is revolutionising the healthcare industry in profound ways. AI in healthcare spans a wide range of applications, from assisting doctors in making more accurate diagnoses to developing personalised treatment plans and accelerating drug discovery. Here we explore 7 key examples of artificial intelligence in healthcare that are driving the transformation towards more efficient, effective and personalised care.
1. AI-Powered Diagnostics
One of the most impactful artificial intelligence applications in healthcare is in the field of diagnostics. AI algorithms can rapidly analyse vast amounts of medical data, including imaging scans like X-rays, CT scans and MRIs, to detect signs of disease that may be missed by the human eye.
- Key applications:
- Detecting lung cancer nodules in CT scans
- Identifying pneumonia in chest X-rays
- Diagnosing diabetic retinopathy in retinal scans
- Leading companies:
- Zebra Medical Vision and Aidoc: AI-powered radiology solutions
- PathAI: AI-assisted cancer diagnosis from tissue samples
The potential for AI to enhance diagnostic speed and accuracy is immense. One study found that an AI system was able to predict breast cancer risk from a mammogram with 97% accuracy, reducing unnecessary biopsies by 30%. As artificial intelligence in healthcare examples like these continue to evolve, AI has the potential to become an indispensable diagnostic aid, empowering doctors to catch diseases earlier and save more lives.
2. Precision Medicine & Drug Discovery
Another key application of artificial intelligence in healthcare is in the realm of precision medicine. By analysing a patient’s genetic profile, medical history, lifestyle factors and more, AI can help doctors develop highly personalised treatment plans tailored to the individual patient.
- Key applications:
- Customising cancer treatments based on genetic mutations
- Accelerating drug discovery by predicting efficacy and safety of candidates
- Identifying new uses for existing medications
- Notable companies:
- Tempus Labs and Foundation Medicine: AI-powered cancer treatment optimisation
- Recursion Pharmaceuticals: AI-driven drug discovery for rare diseases and ageing-related conditions
3. Virtual Nursing Assistants
AI-powered virtual nursing assistants and chatbots are increasingly being adopted to provide 24/7 guidance to patients, assisting with tasks like symptom checking, providing personalised health tips, and answering common medical queries.
- Benefits:
- Improved patient engagement and support
- Reduced strain on overburdened healthcare systems
- Increased accessibility, especially for remote or mobility-challenged patients
- Leading companies:
- Sense.ly and Buoy Health: AI-powered symptom checkers and triage tools
4. AI-Assisted Robotic Surgery
In operating rooms worldwide, artificial intelligence is enhancing surgical precision and dexterity through AI-assisted robotic systems. These advanced robots, like the Da Vinci Surgical System, allow surgeons to perform complex procedures with greater control, flexibility and vision.
- Key features:
- Real-time guidance to surgeons
- Automation of certain surgical tasks
- Enhanced precision in minimally-invasive procedures
- Future possibilities:
- Remote telesurgery enabled by AI and robotics
- Democratised access to top-tier surgical expertise
5. Predictive Analytics for Population Health
Artificial intelligence in healthcare is being leveraged to analyse population-level data and generate powerful predictive insights. By mining electronic health records, claims data, social determinants of health, and even consumer-generated data from wearables and apps, AI can uncover hidden patterns and risk factors associated with certain diseases.
- Applications:
- Identifying high-risk individuals for proactive intervention
- Predicting hospital readmission risks
- Stratifying patient populations by risk level
- Notable platforms:
- Jvion and Lumiata: AI-driven population health management
6. Streamlining Administrative Tasks
Beyond clinical applications, artificial intelligence in healthcare is also transforming back-office operations and administrative functions.
- Key areas of impact:
- Automating medical billing and coding
- Optimising staff scheduling and resource allocation
- Extracting information from unstructured medical records
- Improving revenue cycle management
7. Advancing Medical Research & Clinical Trials
AI is accelerating the pace of medical research and transforming the way clinical trials are designed and conducted.
- Applications in research:
- Analysing vast troves of biomedical data
- Generating new hypotheses and identifying novel drug targets
- Uncovering previously unknown disease mechanisms
- AI in clinical trials:
- Identifying eligible patients
- Predicting dropout rates
- Optimising trial designs
- Analysing real-world evidence for safety and effectiveness
- Notable companies:
- Deep Genomics and BenevolentAI: AI-driven drug discovery
- Antidote and TrialSpark: AI-powered clinical trial matching platforms
The Future of AI in Healthcare
The examples and applications of artificial intelligence in healthcare discussed above offer a glimpse into the immense potential of AI to revolutionise patient care, streamline operations, and accelerate medical research. From assisting doctors in making more accurate diagnoses to developing personalised treatments and discovering new drugs, AI is touching every aspect of the healthcare ecosystem.
While there are certainly challenges to overcome – from ensuring data privacy and security to validating AI algorithms and integrating them into clinical workflows – the benefits of AI in healthcare are simply too great to ignore. As technology continues to evolve and more healthcare organisations embrace AI, we can expect to see even more innovative and impactful applications emerge.
Ultimately, the goal of artificial intelligence in healthcare is to augment and empower human intelligence, not replace it. By working hand-in-hand with AI, healthcare professionals can provide better, faster, and more personalised care to patients, improving outcomes and saving lives. The future of healthcare is being shaped by AI, and the possibilities are truly exciting.
Citations
- Ardila, D., Kiraly, A.P., Bharadwaj, S. et al. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat Med 25, 954–961 (2019).
- Vamathevan, J., Clark, D., Czodrowski, P. et al. Applications of machine learning in drug discovery and development. Nat Rev Drug Discov 18, 463–477 (2019).
- Davenport, T., & Kalakota, R. The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98 (2019).
- Panesar, S., Cagle, Y., Chander, D. et al. Artificial Intelligence and the Future of Surgical Robotics. Ann Surg 270, 223-226 (2019).
- Beam, A.L., Kohane, I.S. Big Data and Machine Learning in Health Care. JAMA 319(13), 1317–1318 (2018).
- Davenport, T. H., & Ronanki, R. Artificial Intelligence for the Real World. Harvard Business Review, 96(1), 108–116 (2018).
- Harrer, S., Shah, P., Antony, B. et al. Artificial Intelligence for Clinical Trial Design. Trends Pharmacol Sci 40(8), 577-591 (2019).
[1] https://bmcmededuc.biomedcentral.com/articles/10.1186/s12909-023-04698-z
[2] https://link.springer.com/article/10.1007/s12553-021-00555-5
[3] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955430/
[4] https://www.sciencedirect.com/science/article/pii/S0933365724000113
[5] https://www.jmir.org/2022/10/e40238/
[6] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10879008/
[7] https://www.sciencedirect.com/science/article/pii/S2666990024000132
[8] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616181/
