AI is a burgeoning new field with applications throughout multiple different industries. Among the most discussed applications of AI is its uses in healthcare. In fact, the National Health Institute has found that in the next two years, the use of AI can reduce healthcare costs in the US by $150 million! From improving patient diagnosis to revolutionizing the way surgery is done, let’s explore the ways AI can transform our healthcare.
- Improved Diagnosis (Precision Medicine)
Precision medicine involves the use of AI algorithms to enhance diagnosis and treatment plans for patients. Data such as age, gender, geography, race, family history, immune profile, metabolic profile, microbiome, genetic information, physiological monitoring data, EMR (electronic medical record) data, and environmental vulnerability are collected. Machine learning algorithms can then use this data to predict how diseases will progress and the optimal ways to treat the disease. Implementations of precision medicine can reduce costs and improve patient responses to prescription drugs.
- Development of Drugs
Developing new drugs is a costly and time consuming process, and many drugs fail to move beyond the development stage. The genetic information, physiological monitoring data, and EMR (electronic medical record) data of machine learning can shorten the lengthy process of developing drugs by analyzing the chemical and biological characteristics of drug molecules (which are stored in online databases) to identify potential drug candidates for the treatment of a specific disease. Additionally, deep learning algorithms, which mimic the decision-making skills of the human brain, can be used to design new molecules. Deep learning systems apply knowledge of existing molecular compounds to create new viable models for drugs.
- Applications in Surgery
AI algorithms can be used to enhance the way surgery is done. Algorithms are “trained” by watching videos of doctors performing surgery to identify which situations call for which surgical procedures. These algorithms can provide assistance to surgeons performing complicated surgery, or inexperienced surgeons forced to perform emergency applications. Additionally, a much discussed topic is surgery performed by robots. Experimental robots like the STAR from Johns Hopkins University have been proven to outperform human surgeons in specific surgical procedures.
- Virtual and Augmented Reality in Training
Currently, many students in medical school learn about concepts without ever actually getting to see, and thus fully understand what is being discussed. VR and AR can be used as a tool for students to learn how to do surgical procedures and better understand the anatomy of the human body. By using VR and AR in the early stages of a student’s training, the cost of training in later stages is lowered as students already have built up familiarity with the skills being taught.
- Neuroprosthetics (Brain Machine Interfaces)
Neuroprosthetics or Brain Machine Interfaces (BMI) can be used as a tool to help those with conditions that impair one’s sight, hearing, cognition, sensory, or motor skills. A device records a patient’s brain signals, which are then analyzed by AI-powered machines to determine which brain signals correspond to which actions. These machines can then perform the desired action.