Applications and prospects of AI in medical health
Artificial intelligence is transforming industries, and healthcare is no exception. Here’s an overview of the promising present and future applications of AI in health.
Precision diagnostics
One major use of AI involves analyzing medical images and data to detect disease and abnormalities with greater accuracy and speed than humans.
AI algorithms can now identify tumors, analyze MRIs for markers of neurological conditions, and scan retina images for diabetic retinopathy more precisely than clinicians. This allows earlier intervention.
As the technology improves, AI diagnosis could become the norm, ensuring no case falls through the cracks.
Personalized treatment
AI enables physicians to create customized treatment plans based on a patient’s genetic profile and medical data.
By scanning records and the latest studies, AI can predict which drugs and therapies have the highest chance of success for each individual.
Personalized AI assistance will help doctors provide the best possible care tailored to the patient.
Digital doctors
Advances in natural language processing mean AI chatbots can now offer basic medical advice with increasing sophistication.
If you describe your symptoms to an AI chatbot, it can recommend possible diagnoses to investigate or suggest home remedies to relieve issues like headaches or sore throats.
While not a substitute for doctors, this technology will increase accessibility to healthcare.
Drug development
Developing and testing new medications is an arduous process. AI can accelerate drug discovery by analyzing molecular data and running countless trial simulations faster than humans could.
In fact, an AI system recently helped identify a new antibiotic able to kill drug-resistant bacteria after just a few weeks – a task that would normally take years!
Gene editing
Gene editing allows doctors to alter a patient’s genetics to treat inheritable conditions. But getting it right requires extreme precision.
By helpfully scanning DNA and calculating optimal edits, AI takes much of the human error out of the process.
This makes CRISPR and other gene editing methods exponentially more accurate and efficient.
Managing records
Maintaining accurate health records for large patient networks is a huge administrative burden. But AIs can seamlessly update records in real-time and ensure critical information isn’t missed.
AI record management frees up staff for more meaningful work and reduces mistakes.
Monitoring patients
Wearable sensors and apps can now continuously gather data like heart rate, glucose levels or sleep quality. But analyzing this requires constant human oversight.
AI simplifies things by reviewing incoming data from monitoring devices to flag any concerning irregularities to medical staff immediately.
Improving mental health treatment
Mental health often relies on self-reported experiences, which AI may struggle to interpret. However, scientists are developing algorithms capable of analyzing subtle verbal cues and language patterns indicative of conditions like anxiety or PTSD.
This data enables more nuanced diagnostics and care. Talk therapy bots are also evolving to serve as basic counselors or coaches.
Prevention and wellbeing
By crunching population data, AIs can determine risk factors for conditions like heart disease or diabetes then suggest preventative steps to the at-risk groups.
Consumer apps fueled by AI now help people manage conditions through education, medication reminders, digital coaching and more.