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Artificial Intelligence (AI) in Healthcare

What is artificial intelligence in healthcare?

Artificial intelligence (AI) in healthcare is the application of advanced computer systems that can analyze large datasets to generate algorithms to provide physicians and healthcare teams with better medical diagnostics, health treatments, cost efficiencies, and medical outcomes. Medical practitioners input relevant data into AI-enabled computer networks that interpret, analyze, and produce solutions for complex medical tasks. Healthcare teams can easily make critical clinical decisions with the help of advanced algorithms that can effectively generate insights from large sets of qualitative data from patient and medical reports.

AI systems use deep learning, machine learning (ML), and natural language processing (NLP) to identify patterns from large datasets to support stakeholders such as researchers, clinical trial managers, healthcare payers, and physicians to make proactive decisions in health management. 

Data insights from AI systems are updated in real-time, giving physicians higher quality feedback from medical devices, sensors, clinical images, and medical notes. With the help of cognitive tools and machine learning, doctors can make more accurate medical assessments, using the insights to create preventative care plans.

AI is reinventing and improving personalized medical care, surgeries, and everyday diagnoses by identifying patterns from data – like medical claims, reports, Electronic Health Records (EHRs), and medical images – and providing healthcare workers with knowledge beyond human computing power. AI machines use input from various medical data to mimic human thinking and make predictions to assist healthcare workers in prioritizing the best care solutions.

How is AI transforming the healthcare industry?

Healthcare organizations that leverage AI technology can improve care interventions and treatment variability. To get the best solutions, healthcare teams must integrate its application into clinical workflows and existing technologies. Healthcare organizations that use AI systems have increased confidence in the quality of insights from complex datasets, helping to support clinical decision-making, daily workloads, and operational outcomes. 

AI machines are revolutionizing healthcare with:

  • Early disease detection: AI can detect early signs of chronic symptoms in cardiovascular and cancer screenings, helping doctors better analyze high-risk patients and when they need further testing.
  • Telehealth diagnostics: Telehealth provides patients with access to immediate care and can be equipped with tools that monitor risk variables, such as heart rate and blood sugar, allowing doctors to assess early detection and update care plans.
  • Medical imaging analysis: AI systems can diagnose disease by analyzing medical images and scans, giving doctors a quick overview of critical information that can help identify early-stage symptoms. 
  • Analyzing unstructured data: Patient data and electronic medical records (EHRs) can be easily accessed by physicians even when the format is not standardized. AI can collect and read through various unstructured data types for quicker report analysis and more reliable medical care. 
  • Genetic medicine discoveries: AI can predict the probability of genetic disease by searching through patterns of compounds and biomarkers and processing the data to look for molecular alterations. The identified compounds can then develop medicines for unmet genetic disorders. 
  • Building platforms for drug innovations: AI can produce insights on new use cases for existing drugs by using automation to comb through large sets of biological and chemical data. New medical applications based on known drugs can be more easily identified and tested to advance biochemical innovations that can lead to better health treatments. 
  • Brain-computer interfaces: AI systems linked with brain-computer interfaces (BCIs) can help patients re-connected with parts of the nervous system responsible for speech and movement. The combined technologies can identify the characteristics of the brain associated with activity and help analyze a patient’s brain signals to translate them into directions. 
  • Advancing radiology tools: AI can improve the diagnostic imaging of scans, x-rays, and MRI readings by providing a complete picture of tissue samples and tumors by mapping genetic properties. 

The benefits of AI in healthcare include: 

  • Patient engagement: Patients directly manage their care with online tools, chatbots, and virtual agents. Telemedicine can be used in real-time for timely health updates and routine management. 
  • Advanced health assessment: Predictive analytics can assist clinical diagnoses and better health treatments by allowing physicians to easily read EHRs from different formats and unstructured data, enabling timely health interventions. 
  • Clinical decision support: AI systems deploy advanced algorithms that simplify reading complex data, reducing medical errors and improving individualized medical treatments. 
  • Enhanced health monitoring: Remote devices, wearables, and health apps use AI to analyze vast troves of health data collected around the clock. Clinicians can use these insights to help patients improve care routines and invest in proactive health support.
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