Artificial intelligence and machine learning are transforming many areas of the healthcare industry. A lot of this has been made possible in recent years because of the sheer quantity of data produced by healthcare providers and the opportunity to identify patterns and augment the capabilities of existing physicians, clinicians and staff. From robot-assisted surgeries to virtual nurse assistants or AI systems helping diagnose diseases, AI technologies are providing improvements in overall care, diagnosis and treatment.
One area where AI is seeing broader adoption is in medical imagery and diagnosis. Through the use of trained image recognition and ML algorithms, AI-enabled systems are providing a second set of eyes on medical images, and in particular radiology images, improving accuracy rates in detecting anomalies in the images.
For many people throughout the world adequate medical care is not always available. Individuals may be located in remote locations where high-quality care is not available, might not have access to reliable transportation, or may be too sick to travel. Additionally people struggle with finding the visit doctors or may be otherwise unmotivated to get the care they need. For these individuals, virtual medical care is making easier to get the care they need. AI applications in healthcare are enabling new levels of care through the use of chatbots and intelligent assistants that are available to patients on-demand 24/7, providing immediate answers to medical questions, personalized care responses and escalation to physicians as needed. These technologies are improving overall quality of care, patient satisfaction and treatment outcome.
To learn more on how AI technologies are being using in medicine, as well as seeing a larger image of Cognilytica’s infographic, click here.