The use of Artificial Intelligence (AI) has rapidly expanded. It can offer innovative solutions to wide ranging challenges. It can enhance efficiency, accuracy, and accessibility in many sectors. In the healthcare sector, the role of AI could extend to diagnosing diseases to streamlining administrative tasks. This article considers the potential roles AI could play in the delivery of healthcare.
Examples of AI in Healthcare
AI in Medical Imaging
AI algorithms can analyse x-rays, MRIs, and CT scans to detect conditions such as tumours, fractures, and infections with high accuracy. Examples of AI medical imaging systems include:
- Automatic processing of scans for patients with prostate cancer. A scan image is taken where the prostate is outlined, the tumour marked up and a report issued. This can speed up prostate cancer treatment and its application may be used in detecting other cancers.
- Technology which analyses CT scans of patients with suspected coronary heart disease. A 3D model of the heart is created helping doctors spot where blood flow is disrupted by blockages.
AI in Diagnostics and Treatment Planning
AI can assist with the diagnosis of diseases. An example of one tool is “C the Signs”. This is a cancer prediction system which can identify patients at risk of cancer at the earliest and most curable stage of the disease. The tool uses AI to check the combination of signs, symptoms, and risk factors during patient consultations. It also helps identify which referrals and investigations the patient might need.
Another example is a technology which can identify sight-threatening eye conditions within seconds, and which then ranks patients in order of urgency for treatment.
AI Powered Physiotherapy
There are ongoing trials in Scotland of an AI powered physiotherapist, “Kirsty”, which is being used to address the high demand for physiotherapy services and reduce waiting times. Same day virtual appointments can be booked, and the virtual physiotherapist engages patients via interactive questionnaires to assess their condition and develop tailored treatment plans.
AI in Operational Efficiency
AI is being utilised for automated decision-making in staff rostering, optimising schedules to ensure adequate staffing levels and improve workforce management. AI has been trialled at an English hospital to identify patient at high risk of unplanned hospital admissions, offering proactive health coaching to manage conditions and reduce emergency visits. This approach led to a 36% reduction in A&E attendances during a trial setting.
Ethical and Practical Considerations
The integration of AI in healthcare raises important questions. How do we ensure data privacy and security? What happens when an AI system makes an error? Addressing these challenges will require a collaborative effort among technologists, medical professionals, and policymakers.
AI is not a cure-all but a powerful tool that, when used responsibly, could revolutionise healthcare. The above examples demonstrate the potential role AI can play in improving patient outcomes and increasing operational efficiency in the delivery of healthcare.
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