Artificial Learning and Machine Learning have already captured many important sectors worldwide, and healthcare is no exception. In the US a well-developed medical and healthcare system allows them to make more inventions. But many countries in Asia and Africa need to develop and enhance their healthcare system. During the pandemic, AI devices worked in the medical industry and helped doctors and nurses treat patients. Many doctors benefited from virtual meetings with patients, monitoring, and keeping electronic medical records of patients, which could consume too much time for medical staff during that period.
AI and ML play their role in the predictions and symptoms of diseases in patients. ML uses NLP (Natural Language Processing), which can make clinical notes and decisions by giving doctors time to look for patients. Though there are some challenges regarding the use of AI and ML in healthcare, there are solutions too. Below are some applications and roles of AI and ML in healthcare sectors.
- Help in Clinical Diagnosis
Diagnosis of patients is one of the time-consuming and challenging processes for doctors. So specialist doctors sometimes take the help of AI to detect and diagnose a patient’s disease to help them recover faster. ML is the subcategory of Artificial Intelligence. It uses software like NLP to memorize large quantities of data and make analyses on it quickly. In some conditions, doctors try to detect the disease in patients when the patient is in the serious phase, so at that time, these AI smart devices and applications can help to predict symptoms, and doctors also can take fast actions.
- AI Chatbots Will Give Primary Care Tips
AI Chatbots are previously trained and defined chatbots that help in different fields to communicate with people by using intelligence regarding that service. AI chatbots are used in business on websites and even in medicine now. Medical Chatbots using AI respond to customers’ queries and schedule appointments easily. If there is a contagious disease like Covid 19, these medical AI Chatbots help to give guidelines regarding disease to people in any language. So it’s accessible to medical staff to use these AI chatbots to light down their workload and give more attention to patients.
- Virtual interaction of Doctors and patients
Doctors can treat patients who are in severe health conditions online. Virtual meetings are possible due to AI-based apps and software that take clinical notes regarding a patient’s symptoms and condition. Emergency patients will surely thank this technology because doctors can be available in time to treat them.
- Help to Keep EHRs
The medical field and hospital have lots of data regarding patients’ history and registers of information which is quite time-consuming work. EHRs are E-registers that keep medical records in digital form. There is no longer a need to hold hospital registers about a patient’s medical history. More than keeping records, a more difficult task is to find and search for people in physical registers. But these EHRs help to summarize all data properly and medical staff.
- Prognosis of Disease
The prognosis of a disease is one of the important steps in treating a patient’s disease. Prognosis refers to the prediction of the progress of the disease in the future. And the Machine Learning system is also run on these predictions using artificial intelligence. So ML is used in medical science to accurately predict and detect that disease’s steps. Disease like Tuberculosis and cancers includes steps of infection. Early diagnosis is a good way to recover patients easily for doctors. So this prognosis process is very important in the medical field.
- Helps Healthcare Professionals
As a part of the medical staff, you need to work 24/7 for patients. But repeated tasks like keeping records and patient’s medical history are a little hard to bear. AI and machine learning focus on these tasks and accurately complete them within time. Electronic Health Records, like software and other healthcare management applications, help nurses and doctors give more time to patients than this lengthy work.
- Robotic Surgery
AI combines with robotics to rise to intelligent robots. During the surgery of patients, it is hard to take fine and delicate incisions. Robots don’t get tired while working, which is beneficial during surgery. Precise decisions are essential in surgery, so robots are trained with ML and have the intelligence to carry out target work properly. So in the future, there will be robots doing our surgeries in hospitals under doctors.
- Inventions in Drugs Industry using AI
AI is now not only for arranging gene sequencing, but it is used for inventions in the drug industry. AI can assist pharma companies in generating medicines and all the other drugs faster. AI devices can identify efficiencies and side effects of any drug used for treating patients. The Drug industry has to do clinical trials after any new pharmaceutical product, but using AI reduces the cost of clinical trials for many pharma companies.
- AI supports Radiology
Image analysis regarding a patient’s disease is one of the main parts of detecting the exact cause of any disease. Radiologists, cardiologists, and Roth specialists types of doctors do image analysis regularly to check out the body’s inner system and find out the exact affected region inside the body. So, AI-based devices are trained by thousands of images for learning and to get the best results after their training. This innovation in image analysis in medical science will surely help professionals and doctors to make conclusions.
- Use of AI and ML in Medical Emergency
Every time it is not easy for doctors and other medical staff to reach the right time on the patient’s door, and the same case with patients. So, in this situation, AI devices and applications play an important part till the doctor is not treating patients. AI and Ml use their intelligence to predict and analyze the disease, making it easy for doctors to treat patients immediately.
Challenges Ahead of AI & ML in Healthcare
- Risk of errors while doing surgery and diagnosis
- Less availability of AI and ML experts
- Sufficient data for training of AI devices
- Robots may cause injuries
- Privacy of data
- Reduction of employment in healthcare
Conclusion
Though AI and ML technology show its benefits and usage in many sectors, and also in the case of healthcare, it should be improved and optimized more to reduce the risk of injury to patients. But technology like EHR is more convenient and useful in healthcare sectors. If other improvements and changes are made in the future in this tech, then AI will become a transformative journey for medical staff and every single patient.