The simulated use of machines and computers to perform human activities expediently and without errors is the feature of artificial intelligence or AI. From robotic surgeries, hospital administration and billing, and pathological research to predictive medicine, AI is helping healthcare enablers reimagine the scale of patient care to a high level.
AI is not just taking over the repetitive and mundane tasks that usually create the bottlenecks in clinical administration for a healthcare facility but also helps in addressing complex problems with backtested solutions. AI in healthcare is changing the landscape of the patient care delivery model and is making the existing sluggish process future ready.
Examples of AI in healthcare
There are scores of tech companies in medical and pharma technology that are involved in using machine and deep learning neural networks to assess complex medical problems that have remained out of the realms of human comprehension till now. This is possible with the extensive data analytics model that can be reviewed within a few minutes using different AI methods. Here is a list of a few areas where AI is either implemented or in a prototype stage which will change the way patient care is perceived forever:
1. Improved emergency medicine
In emergency rooms, time is critical, and a delay of a few minutes can be the difference between the life and death of a patient who is brought often. AI products are now designed to overcome this issue whereby a patient’s history is detected, and the care teams are informed of all the details they will need for effective care. This is particularly important for patients who may have a history of high blood sugar, congestive heart conditions, COPD, or are allergic to any substance. When emergency doctors attend to a patient with complete details, they can stabilize the patient without having to second guess their critical thinking.
2. Improved cancer diagnostics
Biopsy and fine needle tests can often take a long time and may result in errors that are often crucial for accurate diagnostics. AI is helping pathologists detect cancer cells within a shorter span, and that too without errors.
3. Patient engagement tools
Chatbots are designed to listen to patients who can relate their symptoms. The information is then synthesized and shared with the consulting healthcare facility. For generic conditions, the chatbot can also guide the patients for effective care. These tools can ease the workload of nurses and hospital staff for generic questions and still maintain high standards of patient engagement.
4. Early stage diagnostic
Using machine learning information on detecting early-stage blood diseases caused by harmful bacteria are being detected. Physicians fed the machines extensive data for patients’ blood samples who were already affected by the disease. Then AI models learned to detect bacteria from new samples thereby automating the process and increasing the speed of early-stage diagnostics
5. Clinical trials
Clinical trials involve a lot of procedural requirements where healthy volunteers need to be identified as per the mandate of the regulatory restrictions. Using AI, pharmaceutical companies can identify new healthy volunteers for clinical trials of drugs in immuno-oncology.
6. Drug design
Using expansive databases and AI pharma companies can identify potential new drugs and design their formulation, including screening for the feasibility of the market. Pharmaceutical companies can narrow their discoveries to match effective treatments for critical illnesses like cancer.
7. Predict the bioactive of pathogens
AI is helping screen millions of genetic compounds to understand the bioactivity of pathogens. Using neural networks, patients’ status and response results are delivered 100 times faster than traditional pathological methods for disease identification.
8. Robotic surgeries
Simple procedures where a physician or nurse used to stitch up a deep cut are already employed in major hospitals around the globe. But even complex procedures like cardiac surgery are conducted through robotic-assisted tools where the recovery rate is established to be high. Here without disturbing a patient’s chest skeleton automated procedure is conducted by robots.
Conclusion
Healthcare is one space where the use of AI eases the process and helps scores of patients access affordable care in the future. It aids mankind in detecting diseases at a faster pace and without errors so that effective treatment can be used to counter the problem.
Source: Read Full Article