As time goes by technologies become more sophisticated and smart. A new scientific project has shown that artificial intelligence may be able to diagnose disease quite successfully. However, the lack of quality studies means the real potential of the new technology in medicine is unclear.
It focused on an AI technique called deep learning, which employs algorithms, big data, and computing power to emulate human intelligence.
In addition, this learning technique allows digital systems to identify patterns of disease by analyzing hundreds of images, before applying what they learn to individual cases. Afterward, AI provides a diagnosis. Machine Learning has made great advances in the pharmacy industry and upgraded biotechnology efficiency. However, the US Drug and Food Administration already approved a number of Artificial Intelligence algorithms for use in healthcare.
The use of AI in medicine is exciting for everyone. Both AI and medical specialist hope for treatment advances, and a reduction of the workload for overstretched medical professionals. However, scientific research and beta test have failed to live up to the hype.
What is AI good for in medicine?
Well, the AI system is fully capable to function no matter the number of tasks. However, this is why it is ideal for supporting a large population and to situations where human expertise is a scarce resource. AI will be able to support poorly resourced services. However even though machines are wonderful in quick calculating and speedy problem solving, they still lack a human aspect. AI can provide patients with qualities such as empathy and compassion. These characteristics are digital. Furthermore, AI technology is still shrouded by mistrust.
Also, experts say that the global market for AI in healthcare will rise from $1.3 billion in 2019 to $10 billion by 2024. Even though, the mistrust still exists Hospitals around the world are already making use of artificial intelligence technology.
DeepMind, a UK-based AI research center owned by Google has developed an algorithm, that doctors can use in real-time. However, it is a systematic mechanism that makes it possible to return a detailed diagnosis in around 30 seconds using Optical Coherence Tomography (OCT) scans.
Medical experts are able to use algorithms developed by DeepMind. In addition, the algorithm makes it possible to return a detailed diagnosis in around 30 seconds using Optical Coherence Tomography (OCT) scans.
Can we truly trust AI’s medical expertise?
Future AI research should be directed towards carefully selected tasks that broadly align with the trends outlined in this article. It has shown potential in interpreting many different types of image data including radiographs, retinal scans, very general sickness symptoms, and ultrasound. Also, artificial intelligence in robotic surgery holds a very valuable role. However, it will be critical to ensure that AI does not obscure the human face of medicine because. However, AI systems are not sophisticated enough to be independent. Algorithms need more upgrades. For now, AI is not substantially out-performing human diagnosis.
In conclusion, there is definitely a way for AI and humans to collaborate harmoniously in the medical sphere. However, it will take lots of time, machine learning and systematic training to reach that level.
