The most important topic when it comes to the future of medicine and healthcare revolves around artificial intelligence and robotics. For a long time, artificial intelligence was a concept that persisted in people’s minds in a very negative light. Many people still believe that AI innovation could lead to imminent destruction.
Today, AI technology is gradually integrating into many operations and professionals are beginning to realize that it is unlike the common misconceptions. AI is a much-nuanced concept, yet it penetrates every aspect of our lives.
According to a report, artificial intelligence is set to contribute 15.7 trillion dollars to the global economy, having the majority of the impact on the healthcare domain. The Healthcare sector is using AI assistance in an advanced and complex way.
Exciting AI prospects for the next year!
AI in healthcare is showing plenty of promise in the field of healthcare. When it comes to clinical decision support and predictions in healthcare, healthcare professionals can leverage vastly from automation. AI predictive analytics in healthcare technologies can be life-saving for patients. Many AI applications that are being used today in healthcare are enabling practitioners to make a quicker and more precise diagnosis and analysis.
Many companies in healthcare tend to have intensive workloads and require a large amount of computation power to sort data. To help with that, federated learning is an exciting element of artificial intelligence that is making its way into the healthcare field. Nvidia’s Clara federated learning is an AI technology that is integrating with many healthcare procedures.
Using it, healthcare professionals can build robust AI models without moving large amounts of data across different facilities. The federated learning feature further allows data transfer across various patient demographics, institutions, programs, and geographies.
One of the greatest challenges in healthcare is the limitation of data. One of the reasons for this has to do with privacy issues. One of the noticeable improvements in healthcare today is developments in AI automation and software that will leverage patient data and enable efficiency in healthcare modeling.
A federated learning method is an example of AI automation in healthcare. It helps tackle problems regarding Big Data analysis and patient data management. In 2022, data managing technologies are likely to play a key role in imaging software and applications.
Another healthcare area where AI is playing a transformative role in drug discovery. It takes about ten years to develop a new drug. This is because there is plenty of analytics, experimentations, and time-consuming data study which goes into drug discovery.
With the added computational power of artificial intelligence, it becomes a lot easier to study protein ligament interactions, genomic analytics, and all the aspects that help define drug targets. In 2022, AI’s role in drug discovery will be critical, considering the uncertainties of the Covid19 pandemic.
Today, an average healthcare facility consists of many smart devices and computers. A smart hospital environment uses devices like cameras and monitoring equipment to help reduce physician burnout, and also provide a better experience to the patient.
These monitoring devices and data tracking programs also increase operational efficiency and patient satisfaction. They will only get better with time and contribute to the prosperous future of healthcare. These devices play a pivotal role in collecting and storing data.
Machine learning mechanisms of artificial intelligence can use this data and interpret it using algorithms and solve problems based on previous records. In other words, this data will be critical since AI will use it to predict an outcome.
Advancements in Deep Learning
Deep learning in healthcare is a much more advanced field of artificial intelligence. It uses the concept of neural networks to solve difficult problems which require high dimensional data and automated feature extraction.
In 2022, advancements and innovations in deep learning online platforms will allow healthcare professionals to solve higher-dimensional data problems. It utilizes neural networks and maps your input to your output.
To solve a problem in deep learning, you have to make use of these networks. These are networks that imitate the neural networks that are found inside the human brain. They function similar to the human brain, and advancements in the coming year present an exciting emergence of deep learning technology.
Today, deep learning technology has the capability to predict the stage of breast cancer. It models a neural network classifier, studies the breast cancer data set, and predicts whether breast cancer is malignant or benign.
The future of AI in Healthcare
Artificial intelligence in broad terms is any machine that utilizes any kind of intelligence. There are many types of intelligence that lead to the different levels of AI. Nick Bostrom, the author of the book, “superintelligence” separates artificial intelligence into three categories. The first is the level of artificial intelligence that you find today.
He refers to it as ANI or artificial narrow intelligence. This reflects a computer or algorithm’s ability to perform a single task extremely well. In medicine, ANI can be instrumental when it comes to recognizing patterns in huge datasets. These datasets can either be radiology images or other patient data.
The second category in the book is AGI or artificial general intelligence, which refers to a machine that reaches a human’s cognitive capacity. Lastly, the third level of artificial intelligence is one that is still incomprehensible today and poses a threat to humans. He calls this the ASI or artificial superintelligence. This refers to machines learning knowledge of the entire human race and surpassing human intervention.
You cannot tell about the future, but as the year is coming to an end, AI automation in healthcare has looked very promising in 2021. It will be no surprise if it continues to enable the healthcare industry in 2022 in a much-advanced manner, considering regulations and policies that push AI into the healthcare system are already underway.
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