Artificial intelligence is poised to revolutionize the medical and healthcare industries. As artificial intelligence systems progress, the capacities of artificial medical intelligence increase along with its value to all kinds of medical organizations. Today, deep machine learning application in healthcare can help clinicians, medical educators, and other healthcare workers better leverage the ever-expanding pools of medical data to gain insight, improve decision-making, and ultimately drive better outcomes. From automated and assisted medical research and diagnostics, to more sophisticated medical eLearning and CME platforms, artificial intelligence in medicine will help enhance medical training and practice in ways that will drive long-term gains for students, clinicians, and patients.
Introduction to Artificial Intelligence in Medicine
The first generation of AI was mainly concerned with symbolic learning, and was limited mainly to the field of robotics, where basic computer vision and movement algorithms allowed robots to work within tightly controlled environments (such as manufacturing on an assembly line). The latest development in artificial intelligence centers on machine learning, which allows for more sophisticated, human-like analytical reasoning that empowers pattern recognition, probability prediction, and decision making. With contemporary deep learning applications in healthcare, information gathering increases with continued operation and is leveraged to allow AI functionality to be broader, more detailed, and more accurate over time.
Deep Learning Applications in Healthcare
Machine learning in medicine/healthcare generally falls into either supervised or unsupervised learning categories. Supervised learning happens when AI medical applications are fed large amounts of labeled data, and are then subsequently tested on their ability to apply appropriate designations to similar unlabeled data. This is common in medical diagnostic applications, such as those that distinguish between benign and malignant tumors. Human beings review the artificial medical intelligence system's output and correct as needed, which further informs the deep learning application's functionality for improved results going forward. Supervised learning is effectively deployed when the objective is clearly defined, and there are very specific judgments and decisions that the AI healthcare application is meant to produce.
Unsupervised learning represents a perhaps even more exciting line of artificial medical intelligence development. In contrast to supervised learning, unsupervised learning is used when objectives are much broader. It is particularly useful when data sets are enormous, making human research impractical. In medicine, the profound complexity of potential combinations of demographic, health, environment, treatment information, and more that can predict disease and treatment outcomes is often simply overwhelming for human researchers to sort through on their own. Unsupervised deep learning applications in healthcare can empower broader medical research that detects patterns which will give clinicians and educators a better understanding of diseases, treatments, and prognoses than ever possible before. The potential for big data AI machine learning to improve healthcare delivery is inestimable.
Artificial Intelligence in Medicine: Examples
The below list includes just some of the numerous artificial intelligence healthcare applications that show promise for the future.
- Medical/EHR Research
- Medical Diagnostic Assistance Applications
- Pharmaceutical Development Research
- Genetic Research
- Treatment Design
- Clinical Admissions and Treatment Workflow Management
- Personalized Health Monitoring
- Client Relationship Management (CRM) Tools
- Personalized Web UX
- Digital Assistants
- Automated Medical Actuarial Research (e.g., health insurance)
- Patient Scheduling and Information Management
- Inventory Management
In the ever-growing world of healthcare technology, artificial medical intelligence is the key to leveraging the enormous potential of big data in limited time. DDA Medical recognizes this as the breakthrough moment for medical AI. Find out how AI can benefit your medical organization. Contact DDA Medical today.