Intensive Human-machine Collaboration in Healthcare
By MedTech Outlook | Friday, December 07, 2018
Whether machines are computer programmed to perform a human-designed task or designed to assist human beings, the primary parameter that bridges gap between human and machine is the lack of trust. Computer systems integrate technologies like AI to perform tasks that require human intelligence such as decision-making, visual perception, comparison, and translation of languages. It is found to be effective but also prompts warnings regarding job losses and its effectiveness in achieving the desired task.
However, the capability of machine learning algorithms to learn and respond on its own by mimicking the neural architecture similar to the human brain helps the medical sector to take advantage of robots. Notably, in the medical industry where it is required to undergo fewer and small incisions, integrating robots will enhance the diagnostic success rate along with excellent therapeutics.
Michael Stifelman, director at NYU Langone’s Robotic Surgery Center, recently conducted a robotic surgery in patients abdomen using two robotic arms to tie knots with a piece of thread. The third arm is used to guide the suturing needle through the fleshy mass of the patient’s kidney, and final arm is used to hold endoscope to capture that streams visuals in display screens. Individual arm enters into the body with a tiny incision of about five millimeters wide. This tricky procedure has provided a real-time experience of human-robot collaboration in the medical sector.
Another breakthrough of robotic surgery carried out in Washington, D.C., demonstrated a similar edge of stitching the real tissue extracted from the pig’s small intestine; comparative analysis on the performance of autonomous robot with the human surgeon has showcased that bots stitching is uniform with a tighter seal. The insights captured from both the incidents of robotic surgery could eventually lead towards the next level surgical robots with the ability of precise decision making, not only to handle the routine tasks but to take over the entire medical operational responsibilities.
Furthermore, surgeries involving operative tasks such as soft tissue replacement within the chest, abdomen, and pelvic region may pose specific messier challenges. An autonomous robot with advanced decision-making software, brain-computer interfacing, and deep learning abilities can solve these issues along with enhancing patients’ care.
Although robots allow the precise and efficient surgical process in reducing tremors or holding equipment in a place that is impossible to manipulate through the human hand, it is facing barrier regarding data access and high price metrics. The day is not too far when medical-bots will overcome these limitations and take over operating room. Also, the future AI techniques should assist and enhance the surgery rather than taking over the surgeons’ roles.