Medical artificial intelligence is one of the trending technologies in the market. AI is streamlining the workforce by saving time and effort.
FREMONT, CA: AI in medicine has been a huge buzzword in recent months. Moreover, it looks like the trend is here to stay. Like other industries, healthcare is switching to AI to streamline the workflow and to save time and extra effort. There is excellent potential in these modern technologies, and these are revolutionizing the workplace. Here are some of the roles played by AI in the industry:
Role Of Medical Artificial Intelligence
Medical artificial intelligence is one of the new technologies in the market. In medicines, AI detects and analyzes trends from elaborate data inputs provided by medical personnel. This information relates, among else, to treatment methods, their outcomes, survival rates, and speed of care. AI is improving treatment outcomes and reducing costs. As per reports, AI medicine could save the healthcare industry as much as $150 billion annually by 2026.
Medical Artificial Intelligence Can Do Data Analysis
Overwhelming the amount of clinical data is another big challenge faced by the healthcare sector. According to the predictions of researchers in the coming years, the healthcare data will double approximately every 73 days. At the same time, around 80 percent of that data is unstructured. Moreover, AI can read the information and provide a cognitive summary of patients’ records.
AI In Medicine Diagnostics
AI in medicine can diagnose patients suffering from specific diseases. AI is also capable of making faster and precise diagnoses than doctors. Nowadays, doctors have started switching to AI to diagnose cancer patients more efficiently.
Robot-assisted Surgery In AI Medicine
Robot-assisted surgeries are like helping hands for the surgeons. Every year over 5,000 surgical robots are being used in over a million procedures worldwide. Robots can carry out the surgery in a precise manner. AI can also benefit doctors by providing patient records with real-time data during operations, and also by using data from previous successful operations of the same type.