The Impact of Artificial Intelligence on Healthcare: Revolutionizing Patient Care
In the constantly changing realm of healthcare, one technological advancement stands out as a beacon of hope and innovation: Artificial Intelligence.
The emergence of AI has revolutionised numerous industries, altering how we perform tasks, make decisions, predict outcomes, analyse data, communicate, and much more—all driven by data insights and automation.
So, how has Artificial Intelligence impacted healthcare?
One thing that is for certain is our quest to continuously enhance the healthcare system, from new treatments, investments, quality of care and implementing strategies we can work towards a healthcare system that is more accessible and effective in meeting needs of individuals.
Artificial Intelligence has transformed healthcare by improving diagnosis, personalising treatment, and enhancing predictive analytics.
Here are examples of how AI is used in healthcare:
Detecting Skin Cancer: ?
AI can now diagnose skin cancer more accurately than experts. A recent research published in the Annals of Oncology revealed that an AI exhibited a superior ability in diagnosing cancer compared to 58 skin experts. The AI had undergone training using images of skin cancer alongside their corresponding diagnoses. While human doctors accurately diagnosed the condition in 87% of cases, the AI achieved an impressive 95% detection rate.
Eye Health:
Google DeepMind has collaborated with Moorfields Eye Hospital in London to focus on diagnosing two primary causes of sight loss: diabetic retinopathy and age-related macular degeneration (AMD). Through the utilisation of algorithms trained on numerous eye scans, the system identifies potential issues, enabling doctors to swiftly recommend appropriate courses of action with heightened certainty, significantly reducing the time typically required for such assessments.
Read CT scans:
AI can analyze medical images to expedite diagnosis, potentially saving time for radiologists and cardiologists. Radiologists face fatigue and errors due to the high volume of daily image analysis. IBM is developing an AI system to assist radiologists by sorting through images and correlating them with patient health data.
Personalised Medicine: AI is used to analyse genetic data, patient history, and other health records to tailor treatment plans and predict patient outcomes more accurately. This approach allows for more personalised and effective healthcare interventions.
Virtual Health Assistants: AI-driven virtual health assistants and chatbots provide patients with personalised medical advice, answer questions about symptoms, and offer guidance on healthcare services, medication adherence, and lifestyle management.
In summary, AI is reshaping healthcare by speeding up diagnosis, personalising treatment, and improving patient outcomes. The future of healthcare looks brighter with AI at its core.?
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