Can AI Replace Doctors? How Technology Is Shaping Healthcare

Evolution of AI: 

Though the word AI has been in use for a few years recently, the groundwork for it began in the early 1900s with the idea of artificial humans. Later, in 1950, Alan Turing published an article to measure the intelligence of computers, and with that, the term “Artificial Intelligence” (AI) was coined. Later, post-1970s, there was much progress in this field, continuing with the programming language and the idea of robots still being built. After 1980, the period called AI BOOM began, when many governments started funding this idea, and many learnings in the new technology continued to happen, which allowed computers to think independently through programming. Post-1987 till mid-1990 came the period of AI WINTER when AI started to decline due to a lack of income, no returns, and no new development in its field of progress. Post that, there was a surge in the AI AGENTS that were used in research settings, and it gained momentum as the world tried to see its presence when it was used to defeat the world chess player or when the first Roomba was developed, also when AI was used as the first speech recognition software by Microsoft computers. Post 2012, we saw a big surge in AI technology, AI tools, and search engines becoming popular with deep learning and big data.   

The blog mainly focuses on the following: What is AI's role in healthcare? Can AI replace doctors in the future?  

 AI in healthcare started with the field's inception in the 1960s and continues to the present day, when we use AI for diagnosis and treatment plans and for performing surgeries using robots. With the invention of the first chatterbot, Eliza, in 1964, the idea of some artificial intelligence having conversations with humans was made possible. Later, Shakey- the robot was discovered to have acted based on Human instructions, which was a big invention in the field of AI and robotics.. This led to a wide range of possibilities of AI being seen as a challenging field of research, with some tangible reasons. The 1970s saw the beginning of AI tools being used in healthcare with the invention of INTERNIST-1, which helped to diagnose patients based on the algorithm inserted in it as per the symptoms. This saw the possibility that AI has a great future in medicine. 

 Much such research was funded, and scientists cracked their brains to make further progress and development in the field of healthcare using AI. One such innovative idea led to the invention of MYCIN. MYCIN has a set of predefined input data that helps physicians prescribe the correct antibiotics for infectious diseases.  It aided in making healthcare work faster. Next was DXplain, which was a significant advancement that would detect a diagnosis like INTERNIST-1 but with many more clinical diagnoses that a physician can look up. Later in 2000, with IBM developing WATSON, the opportunities in healthcare widened as it was able to take up many questionnaires, which were used for diagnosing a wide array of diseases.  In 2015, PHARMBOT helped in the knowledge regarding the treatment and medications of patients. With COVID-19, the comfort of telemedicine and the use of chatbots increased, and after that, there was a surge in the usage of AI tools in healthcare. 

HOW IS AI USED IN HEALTHCARE?  

With the broad landscape of AI, Machine Learning (ML) is the process of using data, usually collected from statistical learning, to make predictions. It tries to emulate the human brain. Deep learning and neural networks are an integral part of AI and a subset of ML.  

Machine language generates an Artificial Neural Network (ANN) that works similarly to the human brain; it processes data and passes the information to different nodes, like the neural network of the human central nervous system. Convolutional Neural Networks (CNNs) are a subtype of ANN that can both receive and send out different kinds of data. They can also be used to produce complex data to arrive at a diagnosis using disease symptomatology and images. This is much like how a physician's brain works. Computer-Aided Detection (CAD) is another application of ML that physicians use to reduce the chances of missed diagnosis. 

With the invention of Machine Language, the diagnosing process has become easy and non-dependent, like autonomous pathology detection, which, without the assistance of physicians, helps to diagnose the laboratory investigation and gives the result. The chatterbot helps with mental ailments, and it acts like a therapist for patients, who can speak their hearts out without fear of judgment. Since the 1970s, many studies have been done on using ML to assist physicians in not missing a diagnosis for detecting early malignancies, which was [possible using pixel analysis. This helped to identify irregularities in imaging and picked up the malignancies and metastasis without a miss.

Also, new algorithms in ML have been developed to guide magnetic resonance imaging and ultrasound imaging techniques to help physicians with the diagnosis. Thus, using images to interpret the diagnosis is one of the primary uses of ML. It is also used to analyse histological data to screen for cancer. AI has been widely used to detect many skin ailments using trained datasets containing numerous normal and pathological images of skin ailments. And the list of how widely AI is used in healthcare goes on...  

An extensive research effort is underway to attempt to model intelligent behavior without direct human involvement. AI is an integral part of patient information storage, triage, diagnostics, and medical engineering needed in healthcare settings. Bill Gates said at the recent talk show that AI will provide great medical advice and that humans will not be needed for most things in the near future. Many of the research and trials that were conducted on AI vs. doctors showed that the AI detected tools were more accurate than the physicians. What does this mean?   

Will AI replace doctors?  

Well, this is the possibility that we fear for 2050. AI may outweigh the need for doctors, but artificial intelligence will never outweigh the emotional intelligence of HUMANS. These applications are made to aid physicians and reduce their chances of missed diagnoses, not to replace them.   

 Healthcare is all about PATIENT CARE, and the CARE factor is where we will still need HUMANS. AI can complement doctors, but it should, and it can never replace doctors. What we need are doctors who can use AI effectively, and hence, the future of healthcare careers will require doctors who can use AI-guided technology for quick results. AI will make the healthcare system work speedily, but the human caring factor and the human instinct in the diagnosis will always be irreplaceable.

For more such informative articles, visit Docthub.

FAQs:   

Q.1 Can AI replace doctors in diagnosing diseases?  

Yes, AI can replace doctors in diagnosing basic diseases; however, it can never completely replace doctors, as many diseases are diagnosed based on doctors' observations, which AI can miss.   

Q.2 Will AI replace doctors entirely in the future?  

NO, AI can never replace doctors fully in the near future.  

Q.3 What are the advantages of using AI in healthcare?  

AI will aid doctors in taking quick histories and diagnoses, helping with the treatment plan for the patient, and conducting robotic surgeries.  

Q.4 Will AI reduce healthcare costs in the future?  

YES, AI will reduce the cost of the workforce and thus reduce the cost in healthcare settings.  

Q.5 Is AI reliable in predicting diseases?  

AI is not entirely reliable in predicting diseases. As the database fed into the system can be of different settings, and the patient can be in other settings, there is a rare chance of giving the wrong diagnosis in predicting the disease.