With AI networks’ ability to continuously train themselves, there’s a good probability that their performance will improve dramatically in the near future. The use of AI and the Internet of Medical Things in consumer health apps is another interesting deployment. These systems combine medical IoT devices to collect healthcare data, and AI-based apps to evaluate the data and make recommendations depending on the patient’s current lifestyle.
Artificial intelligence technology has proven to be a boon to many industries and has helped solve core problems related to the challenges. It was also beneficial in healthcare, especially when it came to diagnostics. AI is used every time, more in the health care area, according to a recent study published in the Future Healthcare Journal, especially for tasks such as diagnosis and treatment recommendations, patient involvement and compliance, and administrative activities of health workers.
There are exciting opportunities for AI in medicine, how it could improve the treatment process, and some of the most successful AI applications for medical purposes. The use of deep learning in medical diagnostics to detect cancer is an important further development of AI in medicine. According to a study recently published in the Journal of the National Cancer Institute, the artificial intelligence system can detect breast cancer with the same precision as a typical chest radiologist.
With the ability of AI networks to train continuously, there is a good chance that their performance will improve dramatically in the near future. The use of artificial intelligence and the Internet of Medical Things in consumer health applications is another interesting implementation. These systems combine medical IoT devices to collect health data and applications based on artificial intelligence, to evaluate the data and make recommendations based on the current lifestyle of the patient.
The patient-centered approach of medical software developers has created a demand for home health solutions. Artificial intelligence is widely used to treat high-risk diseases. Tele-health tools are being implemented for in-home patients to treat and prevent high-risk situations while reducing hospitalization. Various metrics have to be recorded, documented and processed as a more comprehensive machine of artificial intelligence. This device can warn doctors when a patient is at high risk. This enables early detection, faster diagnoses and a subsequent treatment plan that reduces time and burden of costs.
The best part about using AI in healthcare is that it can be applied in a wide variety of areas, from collecting and processing critical patient data to developing surgical robots. Let’s take a closer look at the five most important medical applications of artificial intelligence:
1. Disease classification
The ability of deep learning technology to examine images and find patterns provides the opportunity to develop algorithms that help doctors diagnose disease faster and more accurately. These algorithms can learn over time and increase their accuracy in guessing the correct diagnosis. Medical diagnostics tests such as MRIs, X-rays, and CT scans, artificial intelligence software, can be taught to correctly identify the signs of a particular disease. Similar technologies that process images of skin lesions have already used artificial intelligence to diagnose cancer.
2. Increasing the effectiveness of decision-making
Diagnostic and therapeutic procedures have always been difficult because doctors must simultaneously examine the patient’s symptoms, possible research errors, all known treatments, possible side effects, diseases with very similar symptoms, and many other factors. Modern AI-based solutions are already helping clinicians master research challenges, process large amounts of health data quickly, and ensure a comprehensive understanding of a patient’s health.
3. Treatment options based on artificial intelligence
Even after a disease has been identified and categorized, the treatment process can lead to further complications. A treatment plan doesn’t just include prescription drugs and exercise. Modern AI algorithms are now helping clinicians develop a comprehensive disease management strategy. Artificial intelligence in medical diagnostics is already a reality, although both healthcare and AI are still evolving and facing many complex difficulties to overcome. Patients can use Google Health to track their physical progress and get insights into their health, nearby hospitals, and medication reminders. A practical example of the usefulness of AI in diagnosis in our country was in Indore when the Apple Watch’s ECG feature saved the life of a 61-year-old man by detecting an irregular heartbeat.
It’s clear that AI is already disrupting the medical business by helping clinics better organize their workflows, make diagnoses and decisions making easier for doctors, and provide critical lifestyle adjustments for patients. Industry experts predict that not only will existing AI-based medical diagnosis solutions be improved, but that new ways to merge AI with medicine will also emerge. For example, AI should accelerate the medication development process.
