Let’s face it – technology is changing pretty fast and the world is changing at the same time. Concepts that were impossible or science fiction before (like AI or Artificial Intelligence) are now becoming totally normal.
Computers that have become powerful enough to handle heavy AI computations or machine learning algorithms are faster and more accurate than ever. The IoT and the cloud have made it possible for small devices to ace AI’s incredible capabilities.
AI is changing healthcare as we know it. Health care is an area where mistakes and recklessness can easily occur which is why it is important for new developments to be regulated and implemented cautiously.
We will discuss five ways that AI and machine learning will be affecting healthcare in the near future:
1.Radiology & Images
Radiology is the form of medicine that deals with images such as ultrasounds, x-rays, MRIs, CTs, and more. This is a healthcare discipline whose specialists spend a lot of time and expertise looking at patients, as well as, images.
This makes it a great fit for AI adoption. Systems, with computer vision technology, can be trained to look at x-rays and apply deep learning to know exactly what images show.
The results of the AI detection can be sent to another specialist for double-checking. AI for radiology is already in use in medical centers and hospitals. For example, in November, the University of Rochester Medical Center announced that it was using tech from Aidoc (AI radiology company) to help prioritize critical cases so that patients could be seen by a radiologist.
As technology improves, it won’t be long before AI radiology solutions are faster and more accurate than human doctors could be. Read more about Machine Learning for Marketers aecost.net/4-key-uses-of-machine-learning-for-marketers
2. Cybersecurity & Intrusion
These new Artificial Intelligence developments in medicine and health care will bring benefits to patients and to all of us. However, they also bring new risks, especially when it comes to security. AI and machine learning can help to provide solutions.
There are medical devices in every hospital. Many AI solutions need to be connected to the internet to make use of cloud-based back-ends. That connectivity gives cybercriminals a potential way in. It doesn’t matter whether or not they are connected to the internet, the medical devices of all kinds are open to communication requests.
Medical centers and hospitals are being hacked at an escalating rate, motivating stakeholders to adopt more serious and strict cybersecurity policies. For example, health care cybersecurity vendor, CyberMDX discovered a certain vulnerability in a syringe pump that could allow an intruder to take over the device and administer dosages of medication.
Artificial Intelligence can certainly help. Advanced cybersecurity solutions could use machine learning to understand network behavior and identify any activities that could indicate attacks.
3. Digital Consultations
Digital consultations aren’t something new. For years now, there have been medical diagnostic systems on the phone or online, for example, WebMD or in the UK – NHS 111 system. However, these systems have their own limitations.
Two developments in Artificial Intelligence have made digital consultations using this modern technology as an option. The development of backend data allows systems to make faster and more informed decisions about what questions to ask. AI digital consultation systems have learned from real case files to ask questions that are relevant to a specific patient.
Advanced natural language processing is the second development and is able to understand sentences rather than ask people to choose predefined options. These AI technologies can help answer questions and recommend actions like going to the ER or making a GP appointment.
Some companies are offering AI-driven digital consultation services. For example, Babylon Health is a startup and is working with Britain’s NHS to add Artificial Intelligence to its 111 services.
4. Personalized Medicine
Personalized medicine is a health care approach where treatments and diagnoses are tailored to meet the patient’s personal history as well as his risk factors and genetics. Many personalized medicine options are crase, however, AI could change that. More and more data is collected by learning models and personalized medicine may easily become a commonplace.
This starts at the diagnosis stage. AI-driven diagnosis is in its beginning stages, but some exciting applications are already being tested. For example, Remidio makes a mobile-phone based diagnosis for diabetes by analyzing images of a user’s eye. This method has been used successfully.
AI-driven personalized medicine may be able to analyze a person’s personal condition and determine what treatments are going to be effective.
5. Robot Surgeons
Artificial Intelligence may also help in one of the most complicated areas of medicine – surgery. There have been robot solutions for surgery for a few years now including the da Vinci system which allows surgeons to take control of robotic equipment and perform procedures.
These, however, are 100% human-controlled machines and not AI. But don’t worry because AI is coming to robots.
STAR or Smart Tissue Autonomous Robot can suture stitches that are cleaner and more accurate than what a human surgeon is capable to do. Early tests show that the technology can successfully remove a tumor with less damage to the surrounding tissue. Without the need for eyes, many of these procedures can be done laparoscopically, making healing must faster.
The official approval process for AI robot surgeons is going to be much longer for those technologies that help doctors do what they are doing. However, at the end of the day, the benefits could be huge.
As you can see AI is coming to every aspect of our lives, from our cars to our homes, workplaces, schools, and etc. Luckily, it is coming to healthcare as well. I am excited to see what’s next. Are you?
Artificial Intelligence is getting pretty sophisticated at doing what humans do but more quickly, efficiently, and at a lower cost. The potential for both robotics
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