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Surgeries are performed by robotic machines, which are controlled by doctors. Robotic surgery is preferred with less invasive techniques, which allow them to perform tasks with better accuracy and control. Mobile ECG monitors and wide usage of smart health watches are utilized for keeping track of and after the surgery. Robotic assistants are employed in elderly care for assisting them in daily routines.

Interfacing the human mind and technology has significant applications in healthcare. Brain-computer interfaces assisted by AI enable patients with neurological diseases to talk, move, and communicate with others. In this scenario, a combination of AI and interfaces decode the neural activities related to the movement of limbs, which further stimulate the indented action.

Immunotherapy is one of the promising cancer treatments. In this therapy, tumors are treated naturally with the human immune system. But a lesser number of patients are responding to these kinds of treatments. Currently, a precise machine learning algorithm is developed to classify and identify the capability of the natural body immune system to treat cancer. AI is also supporting to enable virtual biopsies in the field of radiology, which achieves harnessing image-based algorithms to characterize the patterns and genetic structures of tumors.

AI could reduce the impact on shortages of well-trained healthcare providers by handling over some diagnostic tasks which are allocated to humans. An AI imaging tool take X-rays for tuberculosis symptoms with better accuracy compared to the human. This algorithm is diversified, which considers the environmental factors influencing the disease.