AI is proving to be an innovative addition to the sphere of medicine and has a vast number of uses beneficial for patients and medical institutions and can accelerate the discovery of new knowledge. Starting from diagnostics and treatment and up to pharmacology and drug development, Artificial Intelligence is revolutionizing the sphere of healthcare. Now let us look at some of the primary areas of application of AI in medicine, backed by statistics and data.
Enhancing Disease Diagnosis
There are evidences that show that AI has increased the efficiency and accuracy of diagnosis of various diseases. Such methods how are often very tiresome and they are also associated with a high level of error since they involve the use of human skills and knowledge.
For example in September 2018 Nature published that there were a machine learning algorithms that could do better in recognising the early signs of breast cancer in mammograms than radiographers; the AI achieved a 94.5 percent success rate while the radiologists attained a higher accuracy level of 88%.
Accelerating Drug Discovery
Drug discovery is recognized to be both time consuming, and expensive, which may take more than a decade, and involves billions of dollars to develop a new drug. AI is simplifying this process by estimating the behavior of the chemicals with biological targets and nearly halving the amount of time and money needed.
For instance, Atomwise, a Silicon Valley-based company in the business of AI-powered drug development, utilized AI to forecast the behavior of molecules to find diseases like Ebola and multiple sclerosis’ potential drugs earlier. By what has been said and on what has been written, it can bring down drug discovery time by up to 75% and make it possible to produce effective treatments for diseases which can be quickly and less expensively in terms of resources.
Personalizing Patient Care
The potential application of AI practice in medicine that has attracted a lot of discussion is the ability to deliver personalized patient care. AI makes it possible to assess large quantities of data about genes, life habits, and other aspects of patients’ lives to establish individualized approaches to treatment. This kind of customization not only optimizes the treatments given but also raises the-satisfaction level of the patients.
For instance, IBM Watson for Oncology integrates the patient’s information and based on this, comes up with recommendations that the oncologists can offer based on the patient profile. Research has proved that such personalized treatments by use of AI increases the chances of patient’s recovery by as much as 30%. To learn more, visit this webpage to obtain a better understanding of how AI is revolutionizing precision medicine as well as the patient experience.
Revolutionizing Medical Imaging
AI implementation for diagnostics and imagery is another major application in the field of medicine. Deep learning is used in improving the quality of the input images, reconstructing images of high quality from low inputs while cancer detection can be done automatically.
For instance, the Google’s DeepMind has designed an AI system with capability to diagnose over 50 eye diseases by scanning eye images with a success rate of 94%, and that is as accurate as the top doctors around the world.
Improving Healthcare Operations
Nowadays, AI is enhancing almost every aspect of the health care delivery model that is not directly related to interacting with the patient. AI models can generate a prediction of the patient admission rates and this information can in turn assist the hospitals in giving employment to the right number of employees and proper distribution of resources to increase effectiveness waiting list.
For instance, one survey conducted by McKinsey showed that AI technologies could cut the yearly costs of the healthcare system in the US to $150 billion by 2026 due to optimization of numerous processes and a reduction of costs linked to administrative tasks.
Advancing Medical Research
Deep learning for the generation of synthetic data is going to play a vital role in exponentially enhancing the potential of medical research. This capability is very useful in research fields whereby may be scarce data or limited availability of data as is the case with rare illness.
AI can produce artificial datasets that reflect the real patient information; the researchers can use such data for their experiments without violating the patient’s rights and ethical norms
Enhancing Remote Patient Monitoring
There is also the ever-growing use of AI in the improvement of remote patient monitoring an aspect which has become very crucial most especially given the current COVID-19 times. Artificial intelligence integrated wearable gadgets can also track patients’ health status and identify fluctuations within parameters, including the vital ones, in real time hence enable early detections. For example, Biofourmis, a firm that deals with digital health applications, employs AI in remote heart failure patients’ tracking.
Health care information technology Their AI system can predict potential heart failure events with up to 92% accuracy, preparing the healthcare provider in a position to prevent adverse events before it occurs to a patient. As well as benefiting the patients by enhancing the treatments’ efficacy, this also helps to alleviate the pressure on the facilities because of the decrease in the number of patients returning to the hospital for additional treatment.
Conclusion
Since the advent of AI, it is evident that it has infiltrated the medical field and its applications are numerous including the diagnosis of diseases, the speeds at which drugs are synthesized, to the level of patient care, and the management of the healthcare system. With technological growth, the use of AI technology in resolving healthcare challenges has the potential of offering better results to the patients and health systems.