Artificial intelligence in health care
Artificial intelligence🤖 in health care
Welcome to world of Artificial intelligence. the future Will lead by Artificial intelligence in all areas but today we going to see about
ArtificialI Intelligence in health care so let's jump in to the topic .
What is Artificial intelligence🤖 in health care?
Artificial intelligence🤖 (AI) in healthcare is the use of algorithms and software to approximate human cognition in the analysis of complex medical data. Specifically, AI is the ability for computer algorithms to approximate conclusions without direct human input.
Real life application of Artificial intelligence in health care
1.AI-assisted robotic surgery
Let imagine the future surgery are done by using AI🤖. Is this possible yes With an estimated value of $40 billion to healthcare, robots can analyze data from pre-op medical records to guide a surgeon’s instrument during surgery, which can lead to a 21% reduction in a patient’s hospital stay. Robot-assisted surgery is considered “minimally invasive” so patients won’t need to heal from large incisions. Via artificial intelligence, robots can use data from past operations to inform new surgical techniques. The positive results are indeed promising. One study that involved 379 orthopedic patients found that AI-assisted robotic procedure resulted in five times fewer complications compared to surgeons operating alone. A robot was used on an eye surgery for the first time, and the most advanced surgical robot, the Da Vinci allows doctors to perform complex procedures with greater control than conventional approaches. Heart surgeons are assisted Heartlander, a miniature robot, that enters a small incision on the chest to perform mapping and therapy over the surface of the heart.
2.Image analysis
Currently, image analysis is very time consuming for human providers, but an MIT-led research team developed a machine-learning algorithm that can analyze 3D scans up to 1,000 times faster than what is possible today. This near real-time assessment can provide critical input for surgeons who are operating. It is also hoped that AI can help to improve the next generation of radiology tools that don’t rely on tissue samples. Additionally, AI image analysis could support remote areas that don’t have easy access to healthcare providers and even make telemedicine more effective as patients can use their camera phones to send in pics of rashes, cuts or bruises to determine what care is necessary.
In the very complex world🌍 of healthcare, AI tools can support human providers to provide faster service, diagnose issues and analyze data to identify trends or genetic information that would predispose someone to a particular disease. When saving minutes can mean saving lives, AI and machine learning can be transformative not only for healthcare but for every single patient
3.Unifying mind and machine through brain-computer interfaces
Using computers to communicate is not a new idea by any means, but creating direct interfaces between technology and the human mind without the need for keyboards, mice, and monitors is a cutting-edge area of research that has significant applications for some patients.
Neurological diseases and trauma to the nervous system can take away some patients’ abilities to speak, move, and interact meaningfully with people and their environments. Brain-computer interfaces (BCIs) backed by artificial intelligence could restore those fundamental experiences to those who feared them lost forever.
“By using a BCI and artificial intelligence, we can decode the neural activates associated with the intended movement of one’s hand, and we should be able to allow that person to communicate the same way as many people in this room have communicated at least five times over the course of the morning using a ubiquitous communication technology like a tablet computer or phone.”
Brain-computer interfaces could drastically improve quality of life for patients with ALS, strokes, or locked-in syndrome, as well as the 500,000 people worldwide who experience spinal cord injuries every year.
4 .Developing the next generation of radiology tools
Radiological images obtained by MRI machines, CT scanners, and x-rays offer non-invasive visibility into the inner workings of the human body. But many diagnostic processes still rely on physical tissue samples obtained through biopsies, which carry risks including the potential for infection.
Artificial intelligence will enable the next generation of radiology tools that are accurate and detailed enough to replace the need for tissue samples in some cases, experts predict.
“If we want the imaging to give us information that we presently get from tissue samples, then we’re going to have to be able to achieve very close registration so that the ground truth for any given pixel is known.”
Succeeding in this quest may allow clinicians to develop a more accurate understanding of how tumors behave as a whole instead of basing treatment decisions on the properties of a small segment of the malignancy.
Providers may also be able to better define the aggressiveness of cancers and target treatments more appropriately.
Artificial intelligence is helping to enable “virtual biopsies” and advance the innovative field of radiomics, which focuses on harnessing image-based algorithms to characterize the phenotypes and genetic properties of tumors.
5. Artificial intelligence use machine learning in health tech
To get a better sense of how AI and machine learning are transforming the healthcare industry now, it’s useful to consider specific cases. That is why I have gathered some of the more fascinating applications of the technologies in healthcare right now, which also demonstrate the practical value of these cutting-edge technologies.
👉Identifying tuberculosis in the developing world
Identifying patterns in images is in my opinion one of the strongest points of existing AI systems, and researchers are now training AI to review chest X-rays and identify tuberculosis. This technology could bring effective screening and evaluation to TB-prevalent regions that lack radiologists.
👉Machine learning detect pattern of microbes for chlorea risk
Scientists collect the data of cholrea affected people and unaffected people and feed in to the Artificial intelligence using machine learning .
Machine learning algorithms distinguished those who became ill from those who don't .with trillions of bacteria present in each individual machine learning gives scientists a way to detect suitable pattern that identify diseases susceptibility.
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