Artificial Intelligence is set to change our world, and according to a recent report by Rock Health, machine learning and health AI has already made over $2.7 billion in recent years.
AI in healthcare and medicine will take the shape of using data more effectively through machine learning algorithms which will produce positive outcomes for both patients and medical providers. A great amount of data created through IoT-enabled devices, electronic medical records (EMRS) and ever-expanding quantities of genetic data has already made many changes in healthcare.
The value of AI in healthcare is also that is can enhance human decision-making processes and automate many processes that are time consuming for humans to carry out. The recording of data and using it to provide accurate answers will hugely improve every aspect of healthcare – because AI can operate as a fast and accurate way to help medical professionals make predictions. Hence, AI will never completely replace doctors, but rather is and will empower doctors and nurses by aiding them in data-driven contexts, allowing them to make better informed decisions.
With the right predictive analysis, healthcare can become proactive, rather than reactionary. It can be used to make accurate diagnoses, identify at risk populations, manage and assign administrative resources, forecast the value of research project and predict how patients will respond to medicines and treatment.
AI will unlock great things across the healthcare sector – here are some of the most interesting ways that AI will change the future of healthcare.
As noted, AI in healthcare can aid with predictions – AI can crunch vast quantities of data regarding in-patient volume, types of treatment being administered, and the probable future demand for certain treatments. With this data, hospitals can allocate their budgets more wisely.
“For instance, AI enabled predictive analytics can allow hospitals in any area to know when a flu epidemic will strike. These hospitals can then prepare for the number of ICU beds, flu shots, ventilators and staff they will need to handle the outbreak efficiently,” says Reema Carter, a health writer at 1Day2write and Writemyx.
AI can help human experts in public health know who the most at-risk populations is, rank the severity of an outbreak by analysing population disease data, and automating the administrative preparation process and resource planning.
AI can aid in disease prevention by analysing and predicting entire populations (not just hospital catchment areas). This means that public health can move towards prevention, rather than being rushed of its feet when outbreaks occur. Moreover, a greater understanding of who is at risk will allow preventative guidance that stops these patients entering the healthcare system in the first place!
“Since pathologists spend most of their time looking at tissue samples through microscopes, machine learning algorithms can help them analyse these images. The differences between tissue samples often mean the difference between a diagnosis or not – so having a computer help them do so will save a lot of time, and lives!” Notes Sophia Wooley, a web developer at Britstudent and Nextcoursework.
This is because AI will improve accuracy and efficiency in pathology, the algorithms identifying areas of interest in tissue samples and allowing pathologists to quickly and easily see changes that can be used in diagnosis.
AI can also analyse images in radiology. Usually, radiologist doctors would analyse a set of images gathered from various scans like MRIs or PET scans. Having an AI program on hand to analyse these saves them a huge amount of time and controls human error – AI can detect diseases and anomalies in real-time via pattern recognition. This can be used to diagnose everything from cancerous brain tumours to breast cancer.
Through AI, it’s now increasingly possible to automate drug design and compound selection – that means AI is being used to select the best designs possible, making drug production easier!
Finally, AI can help to compile information using software from companies like Google, APIXIO, Amazon Web Services, IBM and AICure (to name a few). The ease of which this information is recorded and stored, and the manner in which different departments can view the information, will make it easier than ever for healthcare providers to make the right decisions for their patients.
Michael DeHoyos is a content marketer and editor at PhD Kingdom and Academic brits. He assists companies in their marketing strategy concepts, contributes to numerous sites and publications, and is a writer at Origin Writings.