Artificial intelligence (AI) is described as ‘the use of computers and technology to simulate intelligent behaviour and critical thinking comparable to a human being’. It is already utilised in healthcare for ‘online scheduling of appointments, online check-ins, digitisation of medical records, reminder calls for follow-up appointments, drug dosage algorithms and adverse effect warnings while prescribing multidrug combinations’ (Amisha et al., 2019). AI is considered one of the most powerful and successful scientific approaches available today.
AI is creating advancements in the healthcare industry, and one of the most exciting developments is its application in preventative health assessments. It has ‘the potential to improve the diagnostic and treatment decisions, while reducing medical errors’ and has made significant progress in medical imaging and diagnostics. The ‘in-depth learning techniques’ contribute to reducing diagnostic errors and enhancing the accuracy of test results (Wani et al., 2022).
This blog explores how artificial intelligence is revolutionising preventative health by assisting in early detection and intervention to improve patient outcomes and proactive care.
1.The Evolution of Health Assessments with AI
Artificial intelligence has revolutionised the way health assessments are conducted by introducing a new level of precision and personalisation. AI systems can ‘optimise medication dosages, establish guidelines, provide virtual health assistants, improve patient education and influence patient – physician trust’ (Alowais et al., 2023). By analysing large sets of data from various sources, including electronic health records, genetic information, wearable devices, and lifestyle data, AI can identify patterns and correlations that may not be immediately apparent to healthcare providers.
This means that AI-driven health assessments can provide a more accurate picture of an individual’s health status and potential risks. For instance, artificial intelligence can detect subtle changes in vital signs or behaviour that might indicate the early onset of a disease, allowing for timely intervention.
2. Personalised Risk Profiles
One of the most significant advantages of AI in preventative health is its ability to create personalised risk profiles. Artificial intelligence can analyse individual data to tailor assessments specifically to the person, considering their unique genetic makeup, lifestyle, environment, and medical history.
AI systems could consolidate and process input from various data sources, like public health records, optional extra collection data such as microbiome, hormonal, genomic results, and environmental data. By integrating this data into a comprehensive view of each patient, AI would enable tailored health promotion and disease prevention. It could offer services like personalised health coaching, customised recommendations for screenings and immunisations, decision support for clinicians in prescribing preventive medications, and guidance on accessing other public services.
By understanding individual risk profiles, healthcare providers can offer tailored advice on lifestyle modifications, screening, and preventive measures. This personalised approach allows for more accurate predictions and recommendations, enabling healthcare providers to create targeted prevention plans.
3. Early Detection and Proactive Interventions
Early detection is critical in preventing the progression of diseases. Artificial intelligence can help healthcare excel in this area by identifying potential health issues before they become symptomatic. For example, AI algorithms can analyse imaging data to detect early signs of conditions like cancer.
According to breastcancer.org, technicians train AI to interpret mammograms by providing the system with data from hundreds of thousands to millions of mammogram images. The AI software then creates a mathematical model to differentiate between normal mammograms and those that show signs of cancer. By comparing each new image against these standards, the AI can distinguish between normal and abnormal findings. As the AI system is exposed to more mammogram images, it continuously learns and improves its accuracy over time through a process known as machine learning.
Artificial intelligence can assist in the early detection of diseases by identifying abnormalities, detecting fractures, tumours, or other conditions.
In addition to early detection, AI can recommend proactive interventions based on the assessment results. Whether it’s suggesting lifestyle changes, recommending specific screenings, or advising on medication, AI provides actionable insights that can help individuals take control of their health before a condition worsens.
4. Continuous Monitoring and Real-Time Feedback
Another significant benefit of artificial intelligence in preventative health is the ability to continuously monitor an individual’s health. Technological advancements now enable wearable devices to gather data on physiology, activity levels, and biochemical markers. For instance, they can monitor sleep patterns, blood pressure, electrocardiograms (to prevent arrhythmias and coronary heart disease), blood sugar levels, and fall risk.
This continuous monitoring allows for immediate feedback, enabling individuals to make timely adjustments to their health routines. For instance, AI can alert a person to abnormal heart rate patterns that might indicate a risk of arrhythmia or notify someone if their blood sugar levels are trending towards a diabetic range. This real-time feedback empowers individuals to make informed decisions and seek medical attention if necessary.
5. Challenges and Ethical Considerations
While the benefits of AI systems in preventative health assessments are immense, there are also challenges and ethical considerations to address.
Data privacy is a significant concern, as AI systems require access to vast amounts of personal health information. Ensuring that this data is securely stored and used responsibly is crucial.
Additionally, there is the risk of over-reliance on AI, which could lead to overlooking the importance of human judgment in healthcare. AI should be seen as a tool that ‘amplifies and augments, rather than replaces, human intelligence’ (Bajwa et al., 2021) and the expertise of healthcare providers.
How we use AI at Echelon Health
At Echelon Health, we use an artificial intelligence system called AiCE in our CT machine. AiCE is the next generation of CT reconstruction technology. The world’s first Deep Learning Reconstruction method, AiCE quickly produces stunning CT images that are exceptionally detailed and with the low-noise properties you might expect of a future advanced MBIR (Model-based Iterative Reconstruction) algorithm.
This means that highly enhanced images are produced very quickly, which means less time in the machine for the patients and also less exposure to radiation.
We believe that only by utilising the right imaging technology for the relevant disease we are trying to detect. This is why we use a combination of CT, MRI, Ultrasound alongside highly comprehensive blood tests to detect up to 95% of the diseases that are the main causes of early death.
At Echelon Health we understand that everyone wants to live a long and healthy life. Unfortunately, a lot of us will not recognise that something is wrong until symptoms become noticeable.
Preventive Health Assessments are important even if you are symptom-free. At Echelon Health we offer many programmes, however, if a fully comprehensive assessment is what you are looking for, then our Platinum assessment is the one for you.
The Platinum Assessment includes the below tests:
- Medical Questionnaire & Pre-Assessment
- Blood Tests
- ECG
- CT Aorta
- CT Heart
- CT Coronary Angiogram
- CT Chest
- CT Pelvis
- CT Virtual Colonoscopy
- CT Bone Density
- MRI Brain
- MRI Cerebral Artery Angiogram
- MRI Carotid Artery Angiogram
- MRI Prostate
- Ultrasound Thyroid
- Ultrasound Testes/ Ovaries
- Digital Mammogram
- Full Body Mole Screen
- Final Consultation
Flexible Payment Options
We offer flexible payment options across our preventative health assessments to make the gold standard of testing more accessible.
If you have any questions contact our team or check out our health assessment packages for more information on the assessments we can offer you!
Sources:
https://www.breastcancer.org/screening-testing/artificial-intelligence
Wani, S. U. D., Khan, N. A., Thakur, G., Gautam, S. P., Ali, M., Alam, P., … & Shakeel, F. (2022, March). Utilization of artificial intelligence in disease prevention: Diagnosis, treatment, and implications for the healthcare workforce. In Healthcare (Vol. 10, No. 4, p. 608). MDPI.
Amisha, Malik, P., Pathania, M., & Rathaur, V. K. (2019). Overview of artificial intelligence in medicine. Journal of family medicine and primary care, 8(7), 2328-2331.
van der Schaar, M., Alaa, A. M., Floto, A., Gimson, A., Scholtes, S., Wood, A., McKinney, E., Jarrett, D., Lio, P., & Ercole, A. (2021). How artificial intelligence and machine learning can help healthcare systems respond to COVID-19. Machine learning, 110(1), 1–14.
Alowais, S.A. et al. (2023) Revolutionizing Healthcare: The role of Artificial Intelligence in Clinical Practice – BMC Medical Education, BioMed Central. (Accessed: 18 September 2024).
Bajwa, J., Munir, U., Nori, A., & Williams, B. (2021). Artificial intelligence in healthcare: transforming the practice of medicine. Future healthcare journal, 8(2), e188–e194.
