The medical world underwent groundbreaking transformations over the last 20 years to include Artificial Intelligence (AI) in its medical processes. Doctors with more than a decade of experience are struggling to keep up with AI's advanced software which can detect patterns in deep layers of data that infer to the future medical treatment opportunities.
Today, deep learning is fundamental to the survival of established and rising hospitals, pharmaceuticals, and biotech companies. The following questions arise when identifying future goals of medical practitioners -
One of the largest distinctions between AI and medical professionals is the time saved between tests and treatments. AI software can mine through medical records, improve the reading of CT scans and x-rays, as well as detect anomalies that allow for preliminary diagnosis and thus more preventative treatments, all within a matter of minutes.
In 2016, an AI programmed computer completed an in-depth research and analysis on a 60-year-old patient to discover that she was suffering from a rare type of leukemia. The AI took 10 minutes to evaluate what would take doctors weeks to achieve. These are merely a few examples of the ways AI can shape the future of medicine. Wouldn't it be wonderful to receive a diagnosis in 10 minutes instead of waiting weeks? This could be critical for a patient suffering from cancer or more serious illnesses.
Artificial intelligence is more efficient and accurate than doctor originated patient diagnosis. Not only was AI found to improve the outcome of diagnoses by more than 40% accuracy, but it has the potential to save hospitals up to 50% in treatment costs. When AI is used properly, it can enhance early diagnosis, cut down the costs of unnecessary treatments, and transform the future of artificial intelligence in healthcare.
Can artificial intelligence beat dermatologists or any other doctors to an earlier diagnosis is not the only question. Can AI replace doctors in the future, is what's worth finding out.
Leveraging artificial intelligence to expedite patient diagnosis has proven to be increasingly more cost-efficient and accurate compared to traditional means of diagnosis. In 2017, AI software was trained to read over 130,000 images and classify the types of skin cancer. The results proved that AI could identify the most common type of skin cancer (keratinocyte carcinoma) from the deadliest type (malignant melanoma).
When artificial intelligence is programmed for deep learning, it is able to distinguish patterns of cancer, viruses, and illness. Not only does this cut the length of the diagnosis process down, but also makes disease identification a more precise science. Now the application of AI to identify skin cancer has culminated to bypassing dermatologists' 86.6% correct identification percentage to more than 95%.
Artificial intelligence in disease identification is now easier and intervention is faster. Dermatologists and doctors spending hundreds of thousands of dollars to gain field expertise are being outperformed by AI. Through deep learning, the future of AI in medicine has the capabilities to execute simultaneous tasks, process and analyze thousands of images and determine a diagnosis from hundreds of possibilities. Yet the largest obstacle which hospitals and biotech companies face is how to incorporate such important technology into their business.
Companies with established and reputable data science and AI systems understand the importance in implementing such technology correctly in order to reap the most accurate and time-bound results. The development of AI has opened new opportunities for patient diagnosis to be cost and time efficient. The most effective way of maximizing results for patient diagnoses is to outsource this task to a reliable artificial intelligent service provider.
There are numerous substantial rewards of utilizing artificial intelligence in healthcare, including -
We have seen the gradual reconstruction of the medical world that incorporates AI and has considerable effect on medical processes. To conclude, it has been confirmed that AI can beat doctors in patient diagnosis. Here is a simple summary of AI's comparison to doctors' diagnosis -
Needless to say, the future of AI in patient diagnosis is bright, and we will find many hospitals, healthcare practitioners, and healthcare companies rooting for it and utilizing it for highly accurate and fast patient diagnosis.
At Flatworld Solutions, we have an established data science and deep learning center that is well-equipped to integrate AI into your unique business needs. Additionally, we have vast experience in customized software development and can develop unique and intelligent software or apps for your healthcare facility. Our multi-domain expertise allows us to cater to all kinds of healthcare BPO requirements, and develop intuitive software which makes use of Artificial intelligence, Machine Learning algorithms, cognitive computing, and predictive learning.
The standard for expedited accuracy and excellence is understood and recognized throughout our work. We grasp how critical swift analyzing and accurate diagnosis is for your company and your patients. Reach out to Flatworld Solutions to find out more about our revolutionary data science and AI technology!