Medical field professionals will need to learn how to work with all types of technologies incoming, as generally all technological advances in the field have only made diagnostics and patient care significantly easier.
So what is machine learning? Explained more simply, machine learning is essentially a subset of artificial intelligence which takes past data and information, learns and creates patterns based on those without programming explicitly.
To not directly jump into diagnostics and patient care, machine learning as a basis can help in record keeping and data integrity.
Recordkeeping especially when it comes to electronic health records (EHRs) could optimize operations and make it easier for healthcare providers to access the information needed, especially with automating image analysis and providing clinical decision support.
Deep learning is a very complex part of machine learning that imitates the way the human brain functions and is used in detecting objects, recognizing speech, translating languages, and making decisions. Deep learning has found its way into the medical field through mainly detection of images in radiology. Images are presented and through different neural networks that can learn from data without need of supervision, deep learning apps have managed to be able to detect abnormalities and cancerous lesions in medical imaging.
Diagnostics and patient care have the main focus when it comes to AI, mostly because it’s a huge game changer. The technological aspects of developing AI in this field require a different approach which is why it’s more complex.
Administrative applications of the field are not as big of a game changer as diagnostics as patient care, considering that administrative issues can be solved by artificial intelligence in other businesses and corporate worlds. Even though not game-changers, AI being applied in administrative issues in healthcare would change the workflow, giving priority to patient care rather than focus on other tasks that take time away, at the same time to be able to reduce healthcare and administrative costs.