AI has become more sophisticated in doing the things people do, but more efficient, faster, and with less money. Both AI and robots have great promise in health care. AI and robots are becoming increasingly part of our health ecosystem, just as they are in our daily lives.

Now we have selected some examples of how this change is happening.

Maintain good health

People are encouraged to adopt better habits by using technological tools and apps that help them actively maintain a healthy lifestyle. It gives customers control over their health and well-being.

In addition, AI improves the ability of health care providers to better understand the day-to-day patterns and needs of the people who care for them, enabling them to provide more feedback, advice, and support to stay healthy. Permission granted.

It is important to identify in advance.

AI is already being used to diagnose diseases and their early stages, such as cancer. According to the American Cancer Society, a high percentage of mammograms give misleading results, with one in every two healthy women being diagnosed with cancer. AI allows mammograms to be reviewed and translated 30 times faster with 99% accuracy, which reduces the need for unnecessary biopsies [1].

Consumer wearables and other medical devices, in conjunction with AI, are used to monitor and detect malignant episodes in early-stage heart disease, allowing physicians and other caregivers to better monitor and detect malignant episodes. The treatable stage.

Decisions are made

Predictive analytics aids clinical decision-making and action, as well as prioritizes administrative activities, improving treatment by aligning large-scale health data with appropriate and timely decisions.

Another area where AI has begun to take root in health care is the use of sample identification to identify individuals who are at risk of contracting the disease as a result of lifestyle, environment, genetic or other variables - or to worsen one another. To see that happen

Treatment

AI enables physicians to take a more comprehensive approach to disease management, coordinate better care plans, and help patients better manage and adhere to their long-term treatment plans, as well as scan health records for providers to assist in identifying individuals with chronic illness. Adverse event risk.

For more than 30 years, robots have been working in medicine. They range in complexity from small laboratory robots to the most complex surgical robots that can assist a human surgeon or perform surgery on their own. They are used in hospitals and laboratories for support, as well as repetitive work, rehabilitation, physical therapy, and surgery for people with chronic problems.

The end of life help

We live longer than previous generations and as we approach death, we die separately and slowly from diseases such as dementia, heart failure, and osteoporosis. Loneliness is also the most common time.

Robots have the potential to transform lifelong care by keeping patients independent for longer periods and reducing the need for hospital and care facilities. AI, coupled with advances in humanoid design, allows robots to move forward, allowing people to 'talk' and other social interactions to sharpen aging brains.

Research

The journey from the research laboratory to the patient is lengthy and expensive. According to the California Biomedical Research Association, it takes an average of 12 years for a drug to reach a patient from a research laboratory. For every 5,000 drugs that begin preliminary testing, only five reached the human test and only one in five are authorized for human use. In addition, it costs an average of $ 359 million per business to develop a new drug from a laboratory to a patient [1].

One of the recent uses of AI in health care is drug research and development. AI has the potential to be used to accelerate drug innovation and reconstruction processes.

Training

AI allows people to be trained through intuitive simulations that basic computer-based algorithms cannot do. Due to the emergence of natural speech and the ability of the AI machine to quickly draw from the vast visual library, answering a trainee's questions, decisions or recommendations can be challenging in ways a person cannot. In addition, the training program can learn from the trainee's advanced answers so that they can change the challenges regularly to meet their learning needs.

And training can be done anywhere; Because AI is included in the smartphone, fast catch-up sessions are available at the clinic or after a tough case while traveling.