We are well aware that chronic and incurable diseases are on the rise worldwide. When diseases like SARS and EBOLA were emerging, they spread like wildfire. These diseases spread rapidly on the global level and the outbreak must be dealt with quickly so as to minimize the number of people who get infected.
There had been significant improvements in controlling the communicable diseases but we still do not have effective medicines for the disease like tuberculosis, malaria, HIV etc. The recent advancements in the medical field have managed to prevent, diagnose and treat certain diseases like breast cancer, leukemia and many more. According to the recent report by the World Health Organization, the chronic diseases are expected to rise at the rate of 57 percent. But the artificial intelligence applications and advancements will minimize the cost of treating the chronic diseases. Some of these technologies include genomics, stem cell and organ therapy and robotic surgery.
Technology has revolutionized the medical field with it applications. Some of the examples are:
Artificial intelligence is a buzzing word that is here for quite some time now. It has revolutionized almost every field of concern. Artificial intelligence is the branch of computer science that helps in the making of intelligent machines. These machines have the ability of reasoning, perception, problem solving and decision making. These machines have the capability to get better and improve over the time.
Let us now have a look at the role of artificial intelligence in healthcare.
Virtual Health Assistants and AI Chatbots help patients in a number of ways. Virtual assistants are built using artificial intelligence and machine learning algorithms that can help the patients in keeping track with the prescribed medications by sending a timely notification. Moreover, virtual health assistants can give advice on the treatment of the disease and can suggest the patient restrict the diet.
Data science services have the capability to reduce the costs of treatment by 50 percent and have improved the outcome to almost 40 percent. Artificial intelligence machines have improved the precision and accuracy of treatment and reduced the percentage of human error. Doctors are able to get the information about the patient’s condition via patient monitoring systems. Deep learning services have also managed to save millions of dollars in the patient treatment. Some of the areas where artificial intelligence applications have helped in cost-cutting are robot-assisted surgery, connected machines, virtual assistants, cybersecurity, dosage error reduction and many more.
Machine Learning applications are helping the medical field by improving the monitoring systems. The medical monitoring equipment attached to the patient’s body monitors the fluctuations in various health parameters like heart rate, pulse rate, body temperature etc. The data is stored in the patient's database. Digital image processing system is made intelligent enough to sense any abnormal fluctuations in the vitals of the patient. It then immediately informs the doctor concerned about medical condition over the mobile app. Moreover, the doctor also gets the daily reports of the patients that helps them to better understand the condition of the patient.
Billions of dollars are spent every year in the medicinal research. Medical experts, doctors, physicians are continuously researching new and effective drugs for diseases. This can take several years. Take an example of Ebola virus. The antidote for Ebola virus was made in several days with the help of data science algorithms. It would definitely take several years for humans to make that antidote. Imagine how much damage would have done by then. AI and machine learning algorithms speed up the process of drug research and have the capability of saving millions of lives.
Machine learning algorithms and digital imaging have made computer vision to be one of the most remarkable technology. There are immense applications of computer vision in the medical field. Microsoft is working on its image diagnostics tool named ‘InnerEye’ and the results are amazing. It is able to detect the patterns in diseases using 3D imaging and digital image processing. Deep learning neural network is going to become more and more powerful and accessible. However deep learning has a limitation that it cannot give valid explanations of how it reached a particular conclusion. This problem is amplified in healthcare because doctors cannot take decisions without understanding how machine arrived at that conclusion.
Artificial intelligence applications have the ability to redesign the treatment plans. Doctors can now search database such as modernizing medicine and medical assistants to collect the patient information from various sources. Data mining services help the doctors to find out the patient information and the better treatment of the patients. It also helps in the personalized treatment by finding the comparable cases.
Healthcare is having an abundance of data. It is creating a huge amount of data on the daily basis. In the current scenario, Electronic Healthcare Record use is used for storing the medical data. But due to the overload of data, EHR is not able to handle the huge amount of data. The introduction of machine learning algorithms in EHR has automated the repetitive tasks and has saved a lot of time of the user. Users have to perform tasks like clinical documentation, patient entry, and sorting. Voice recognition using Natural Language Processing can help in a speech to text conversion which can be used for later reference by the patients and doctors.
Artificial intelligence has come out to be as a boon to the healthcare sector. Various machine learning services have mitigated the risk factor by improving the efficiency in the treatment. The cost involved in the healthcare can also drop due to the artificial intelligence applications. The treatment will become more and more accessible to the remote areas as well. AI and machine learning have speeded the diagnosis of the patients and help in faster recovery.