Role of AI in Disease Diagnosis and Treatment
Within the healthcare industry, making timely diagnoses and treatment plans makes a massive difference for patients who are searching for preventive medicine or those who are already in the midst of a serious condition. Fortunately, Artificial Intelligence (AI) is improving how quickly doctors and other medical professionals can evaluate and prescribe treatments to patients in need.
Due to its rapid development, AI and Machine Learning are already being implemented in many ways within the healthcare industry, giving doctors insights into how to help patients with advanced medical imaging and predictive analytics. These allow professionals to create more personalized treatment plans that can change lives, so how do they work?
History of AI in Medicine
AI’s use in medicine can be traced back to the 1960s, shortly after AI was conceptualized. Dendral, a rule-based expert model developed at Stanford, was used to study molecular structures. While the model was not directly a healthcare system, it showed how self-learning machines could be used to help study biology and influenced future rule-based expert systems in healthcare.
By the turn of the century, new developments in Deep Learning and the rise of the internet allowed algorithms to train themselves on massive amounts of new data being generated online and in medical facilities. These advancements improve computer vision and other techniques that give medical professionals more detailed insights into medical imaging from X-rays and MRIs, further improving their diagnosing abilities.
AI in Disease Diagnosis
Disease diagnosis is one of the most important aspects of the medical profession because it determines what the treatment for patients will be going forward. That’s why it is so important because an inaccurate diagnosis will not make conditions worse. However, AI isn’t just increasing the speed of diagnosis, it is paving the way for more advanced technology to reshape our current practices help identify issues more accurately and even find new conditions that may have gone unnoticed.
Medical Imaging: Imaging is highly important because it gives medical professionals an insight into the human body. This can reveal a variety of different problems such as cancer, internal bleeding, and more. Applications like DeepMind, Aidoc, and Zebra Medical Vision are all pushing the limits of how key information about a patient can be gathered and acted upon.
Predictive Analysis: Examining historical records with AI can give doctors a deeper insight into the overall health of a patient and find patterns that may explain unknown causes of disease.
Genomic Sequencing: More advanced AI models allow medical professionals to take a comprehensive look at a patient’s complete DNA sequence so that they can identify genetic traits and conditions that require more intricate treatment, but also help patients undergo better preventative care.
AI in Treatment
Not only is AI assisting with diagnosis, but it also helps doctors create better treatment plans by streamlining processes and automating tedious tasks that give doctors more time to develop personalized approaches to a patient’s conditions.
Personalized Treatment Plans: Using vast amounts of data from historical records, genomic sequencing, and other lifestyle factors, doctors can suggest treatment plans that are tailored to individual issues.
Drug Discovery and Development: AI models can evaluate body chemistry and how each individual reacts to certain drugs and medications, providing insight into more effective prescriptions.
Robot-assisted Surgeries: Robotics and AI are paving the way for advanced technology in the operating room where doctors can use machines powered by AI to make surgical procedures safer and more effective.
Potential Challenges and Ethical Considerations
Like most issues involving AI, there is strong opposition to how personal data is collected and used to train AI for medical and advertising purposes. This can be an even more serious concern to many who are especially worried about private data related to their medical insurance and sensitive issues being shared against their will or awareness.
However, a growing concern is the over-reliance on AI that can come about from so much gained efficiency. As these machines become more complex, medical professionals will have to rely less on their own intuition and follow what machines suggest. While this can help with more accurate diagnosis and treatment plans, it can create a level of distrust between doctor and patient that could lead to more harm than good.
Future Prospects
As time goes on there is no doubt that AI will continue to grow and evolve, becoming more beneficial to healthcare workers around the world. With stronger predictive analytics and more emphasis on real-time patient monitoring, the future of the healthcare industry couldn’t look better.
However, there are more than just improved features that already exist. Quantum computing and neural interfaces are opening up new potential for even more powerful medical procedures that could reshape the entire way we treat patients with medicine, creating some of the most effective treatments and diagnoses possible.
