AI-powered diagnostic tools can analyse patient data and provide more accurate and timely diagnoses for conditions like cancer, heart disease, diabetes, etc.
This is an exclusive interview conducted by Santosh Vaswani, Editor at CIO News with Kapil Tyagi, CTO at Artemis Hospitals.
Artificial intelligence (AI) plays a valuable and growing role in patient care across various aspects of the healthcare industry. It has the potential to improve the efficiency, accuracy, and quality of healthcare services. Here are some of the key roles AI plays in patient care:
Electronic Health Records (EHR) Management:
AI can help streamline the use of electronic health records, making it easier for healthcare professionals (doctors, nurses, and paramedics) to access and update patient information. Natural language processing (NLP) can extract relevant information from unstructured clinical notes. EHR helps doctors and patients track their medical history and results as and when required.
Predictive Analytics and Early Warning Systems:
AI can use patient data to predict disease outbreaks and epidemics. In hospitals, it can be used to predict patient deterioration, helping healthcare providers intervene early. Sending real-time alerts through an analytics tool to patients and doctors. Doctors can help patients and provide precautions to prevent future illnesses.
Diagnosis and Disease Identification:
Artificial intelligence can assist in the early detection and diagnosis of diseases. Machine learning algorithms can analyse medical images (X-rays, CT scans, and MRIs) and help identify abnormalities, such as tumours, fractures, and other conditions.
AI-powered diagnostic tools can analyse patient data and provide more accurate and timely diagnoses for conditions like cancer, heart disease, diabetes, etc.
Treatment Personalisation:
AI can analyse a patient’s medical history, genetic data, and other factors to recommend personalised treatment plans, including medication dosages and therapies. Predictive analytics can help identify the most effective treatments for individual patients based on their unique characteristics.
Remote Patient Monitoring:
Wearable devices and IoT sensors can collect patient data and transmit it to AI systems, enabling continuous remote monitoring of vital signs and health parameters.
Telemedicine also plays a critical role in remote patient monitoring, and it cuts down on patients’ travel costs and infection risk.
AI can alert healthcare providers if a patient’s condition deteriorates, allowing for timely intervention.
Patient Engagement and Education:
Chatbots and virtual assistants can provide patients with information about their conditions, medications, and treatment plans.
Artificial intelligence-driven chatbots can also assist in appointment scheduling, medication reminders, and alerts to the doctors.
Administrative and Workflow Optimisation:
AI can help healthcare organisations optimise their administrative processes, such as appointment scheduling, billing, and resource allocation.
It can improve the efficiency of hospital and clinic operations.
Radiology and Pathology Assistance:
AI can assist radiologists and pathologists in identifying and classifying abnormalities in medical images more quickly and accurately. It helps to provide treatment to the patients on time.
While AI has immense potential in patient care, it also raises ethical and regulatory challenges, such as data privacy, algorithm transparency, and accountability. Healthcare providers and organisations must navigate these issues while harnessing the benefits of artificial intelligence to improve patient outcomes and the overall quality of care.
There is a significant need for more specific ethical guidelines for the use of artificial intelligence in medical applications, particularly in nursing. Future research could seek to address this gap by developing practical and context-specific ethical guidelines for different types of AI applications. These guidelines could provide much-needed direction for developers, users, and regulators of AI systems in healthcare, ensuring that these systems are used in a way that respects the rights and dignity of all stakeholders.
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