Artificial Intelligence in healthcare and Investments now is a wide topic to discuss. Artificial intelligence is growing higher now in healthcare used to narrate the use of machine-learning algorithms and artificial intelligence (AI), to resemble human awareness in the investigation, demonstration and understanding of complicated medical and health care facts and figures.
In the next decade, artificial intelligence will become more involved in healthcare delivery. Smart machines will help doctors diagnose conditions and recommend treatments. They will also keep track of patients’ health data and provide feedback to doctors and patients.
AI can help healthcare providers to become more efficient and improve patient care. For example, a computer system can review a patient’s medical records and identify any potential risks or problems. AI can also help doctors to make better decisions about treatments.
AI can also be used to improve patient communication. For example, a computer system could remind patients when they need to take their medicine or book an appointment.
AI will also play a role in the development of new treatments. For example, computers can be used to design new drugs and to test them for safety and effectiveness.
There are many potential benefits of using AI in healthcare. However, there are also some dangers that need to be considered. For example, it is possible that AI could be used to make decisions about treatments without input from doctors. It is also possible that AI could be used to track and store patients’ personal data.
AI depends upon proper data
As AI depends upon data to apply computer algorithms to approach the nearest conclusions based purely on input data. The more proper data results more proper insights. To achieve more closer predictions, machine learning models must be trained using large amounts of proper input data. (large amounts of data through electronic health records for disease prevention and diagnosis).
Artificial intelligence does this job through machine learning algorithms and deep learning. These algorithms can identify specimen in behaviour and create their own logic and rules.
Course of actions: Behaviour
AI algorithms behave diversely from humans in two practices:
1. Trained AI Model:
Algorithms are literal: once a goal set, and training completed the algorithm has learnt only from the input data and can only understand what it has been feed as a programme to do.
Some deep learning algorithms can predict with extreme accuracy, but the resulting figures will not comply to 100% accuracy that depend upon the correctness of data off course.
Health Related AI Applications
The basic focus of health-related AI applications is to inspect connections between proper treatment techniques and patient end results. Utilisation of AI applications are to have practices such as identification processes, treatment development, drug development, individual medicine, keeping track on patients and care.
Famous Medical Institutions using AI
A few medical institutions such as the British National Health Service, Memorial Sloan Kettering Cancer Center, and The Mayo Clinic, have developed AI algorithms for their departments. Similarly large scale technology companies such as Google and IBM have also developed AI algorithms for healthcare. Individual companies are also developing technologies that help healthcare to improve business operations through increasing utilisation, reducing length of stay, decreasing patient boarding and optimising staffing.
Government Investments in AI for Healthcare
Currently, the governments of many countries are investing billions of dollars to progress the development of Artificial Intelligence in healthcare, for example United States government, Federal Ministry of Health – Germany.
Several communities in medicine have shown an increase in research regarding AI. As the novel coronavirus devastates through the whole world, the United States is estimated to invest more than $2 billion in AI related healthcare research for next 5 years.
Currently Active AI Research and Implementations in Healthcare
There are a number of current AI research and implementations in healthcare. IBM’s Watson is a cognitive computing system that has been applied in a number of industries, including healthcare. Watson’s capabilities include understanding natural language, learning by experience, and generating hypotheses. Watson has been used in a number of applications in healthcare, including the development of a decision support system for oncology, the identification of features for predicting sepsis, and the diagnosis of rare diseases.
Another example of AI being used in healthcare is Google’s DeepMind. DeepMind is a machine learning system that has been applied in a number of fields, including healthcare. DeepMind has been used to develop a machine learning algorithm to predict acute kidney injuries, to develop a system to predict the probability of patient deterioration, and to develop a system to improve the efficiency of NHS hospitals.