The applications of AI in healthcare span everything from administrative tasks to assisting with complex surgeries. Here are 10 applications of AI in healthcare that are already showing benefits to healthcare professionals and their patients:
AI algorithms can be trained to analyse patient data such as medical history, lifestyle choices, and genetic profile to detect diseases earlier. This includes the use of electronic health records (EHRs) to predict the likelihood of chronic conditions such as diabetes or cardiovascular diseases. The system may then suggest diagnoses based on these predictions, providing decision support to clinicians.
Studies show AI-assisted diagnosis of myocardial infarction with high accuracy, unaffected by factors like age or gender.
AI can analyse medical images from X-rays, MRIs, CT scans, and ultrasounds, enhancing image quality and identifying patterns or anomalies indicative of diseases. Preliminary reports can then be automatically generated to highlight areas of concern for radiologist review, speeding up the diagnostic process.
The NHS highlight how AI imaging is already helping them on their website, saying
“AI is already helping doctors and other healthcare workers to screen more efficiently for some diseases, including cancer. The ability of AI solutions to identify potential areas of concern in an image more quickly and relentlessly than a human, is helping the NHS to recover from the backlog of patients caused by the pandemic.”
Using virtual assistants or chatbots to handle initial patient inquiries, assess symptoms, and determine the urgency of medical issues can help direct patients to the appropriate level. This can improve efficiency for all case types, reducing waiting times by avoiding unnecessary interventions for low-level care and ensuring that critical cases are attended to promptly. Progress has already been seen in gastroenterology, one of the most pressured NHS specialties.
Traditional pagers lead to miscommunication, delays and data protection issues, with many clinicians turning to social platforms like WhatsApp to communicate. AI-powered alternatives provide more intelligent and context-aware notifications to healthcare professionals, prioritising alerts based on urgency and ensuring that critical information reaches the right person at the right time. Integrating EHRs and EPRs provides real-time updates and patient information, streamlining workflows and reducing response times.
Learn more about how Alertive is using data to streamline clinician communication here.
Automated systems can schedule and manage appointments more efficiently to reduce wait times and pressure on administrative staff, as well as send automated reminders to patients to reduce no-shows. AI can facilitate better communication between patients and healthcare providers through feedback collection, automated follow-ups, and personalised help delivered via apps or messaging platforms.
Using AI to analyse patient data makes individually tailoring treatment and rehabilitation programmes a lot more efficient. Lifestyle, genetic information, medical history, and preferences can all be used to create a more personalised experience that enhances recovery outcomes and improves patient experience, even predicting drug response in cancer patients.
Translating in real time through AI translation tools assists healthcare providers in communicating with patients who speak different languages, improving their chances of receiving appropriate care. Some specialised products on the market are even designed to handle complex medical terminology, ensuring that translations are accurate and contextually appropriate.
AI-powered robotic surgery systems assist surgeons in performing complex procedures with enhanced precision and real-time guidance, reducing the risk of human error. AI also analyses preoperative data, helping surgeons plan the best approach for surgery, improving outcomes and reducing recovery times for their patients.
AI algorithms can detect patterns of fraudulent claims by analysing large datasets, identifying anomalies, and flagging suspicious activities. The NHS Counter Fraud Authority estimates that the NHS is vulnerable to £1.264 billion worth of fraud each year, so advances in AI fraud detection have the potential to save significant amounts of money.
Epidemiological modelling can be AI-assisted to simulate the spread of infectious diseases, helping public health officials plan and implement effective interventions. Models use data from various sources, including social media, travel patterns, and climate data, to predict and monitor disease outbreaks. The value of this cannot be understated in the wake of the COVID-19 pandemic.
With AI already enhancing patient outcomes and improving life for staff, and the impact of AI in healthcare expected to continue growing, it won’t be long before we see this list expand even further as new potential is explored.
