From assisting physicians with diagnostics to sophisticated surgeries performed by robots, the future of artificial intelligence (AI) in the field of medicine and healthcare looks promising. It will influence the market as well. AI can help older, larger biotech firms and Big Pharma companies to assess the market and estimate the value of startups that develop breakthrough technologies and drugs. Armed with that information, leaders of companies can do mergers and acquisitions that can increase the capitalization of their brands.
Using AI for Medical Diagnostics
Professionals often prefer to use the term “augmented intelligence,” since AI is not set to replace human doctors but merely improve their capabilities.
The roles of physicians are already shifting due to the introduction of artificial intelligence in diagnostics. New doctors have to be trained to apply clinical informatics to eliminate errors and improve patient outcomes.
Exams for future physicians already include questions about using AI in healthcare. On the other hand, computer scientists and engineers are claiming their place alongside geneticists and pharmacologists in the field of medicine by putting this technology to work in ways that advance medical science.
From identifying early-stage cancer to reducing human errors and allowing physicians to examine more patients, AI in diagnostics is a welcome development. Using pattern recognition, AI allows doctors to make better decisions faster, saving time and improving chances of survival for patients with severe, hard-to-diagnose conditions.
What Augmented Intelligence Can Do Already:
- Use mobile coaching to collect data in real-time and help patients diagnose minor problems.
- Improve the quality of service for people treated through telemedicine.
- Provide personalized diagnosis and health advice based on patient data from genetic information.
- Scan various images, from x-rays to ultrasound, and provide a preliminary diagnosis.
- Reduce diagnostic errors that account for 60% of all errors made during patient treatment.
- Find bleeds on the human brain, reducing the workload on radiologists.
- Measure blood flow in the brain to help paramedics identify stroke victims.
- Examine images of the eye for signs of diabetic retinopathy.
- Detect wrist fractures in elderly patients.
- Diagnose lung and liver cancer.
- Discover breast lesions and other abnormalities in the chest region and calculate the risk of their malignancy.
- Measure the amount of calcium in coronary arteries to predict cardiovascular diseases.
- Deploy modern, AI-powered apps that can be run on any smartphone to help patients in rural areas where qualified medical help is out of reach.
Drug Development and Testing
In addition to diagnosing a patient’s condition, machine learning health care applications include speeding up drug research and managing entire hospitals.
Machine learning can be used to discover certain patterns by going through vast amounts of data too complex for the human brain to analyze. AI can reduce the discovery stage from months to mere hours.
Pharmacology, especially drug discovery, can benefit greatly from algorithms able to analyze gigabytes of data in minutes. Traditional drug trials often take too much time before a workable treatment that has negligible side effects can be found. Augmented intelligence will speed up the research for more effective cancer treatments, vaccines against deadly viral diseases, and even cures for genetic illnesses.
Managing Pain with VR
Still a developing field in healthcare, pain management can benefit from mixing AI and virtual reality to create immersive, responsive environments. This technology can help distract patients from pain and reduce their dependence on drugs. An approach that might even become a solution to the opioid crisis that ravages the U.S. and other countries of the western world.
Another, more obvious application of virtual reality is to create simulations for doctor training. Some surgeons are already training with these programs which allow them to perform rare, complicated operations without risking the life of a patient.
Health Knowledge Services for Patients
With lots of interactive health and fitness apps on the market, users can choose the ones that offer options like self-diagnostics and general health advice. Unlike human doctors, however, apps can interact with their users 24/7, providing them with relevant feedback.
Developers place a lot of emphasis on accessibility and ease of use, creating software that can provide data in the form of dashboards and other graphic interpretations. The alternative option is to use health-bots — chatbots that can help patients assess their well-being through a dialogue.
These bots can be relatively simple algorithms that react to certain keywords or sophisticated programs that apply machine learning to increase their efficiency and usefulness. Such apps can access vast databases of medical knowledge and give precise answers supported by scientific data.
Improved Patient Logistics
The scope of AI applications is almost limitless. Some of the more creative approaches involve mixing medical and traffic data. Such applications can assign the level of urgency to a patient and calculate the shortest route to the nearest healthcare center that has relevant facilities.
Another application involves in-house logistics where every patient gets an optimized treatment route. This can shorten their time spent in a hospital by improving the efficiency of diagnostics and treatment. Assisted by AI, physicians will be able to make better, faster decisions, using only necessary tests and treatment plans.
Artificial intelligence is set to shape the future of medicine the way genetics and advanced chemistry did in the past. From better-trained doctors and better-diagnosed patients to increasing the overall efficiency of a healthcare provider and researching new, lifesaving drugs with ease, AI provides possibilities limited only by human imagination.