Dangers of Using Internet Search Engines for Self-diagnosis
TECH HUB
Ayodeji Ake writes of the addictive habit of self-diagnosis and the reliability of health information in search engines resulting in increased morbidity and mortality statistics
The advent of technology has made research easier on search engines like Google, Wikipedia, etc., through the use of computers or internet-enabled phones.
Unfortunately, recent reports have revealed that a large number of people utilise the internet to search for health information especially on medical symptoms and medication, consequently, leading to an increase in morbidity and mortality rates.
In medical terms, this is called self-diagnosis.
Over time, medical experts have advised that it is safer to patronise health technology applications that have treated health data rather than relying on search engines that consist of rigid literature that demands health practitioners to break down.
Speaking with a medical expert, Dr. Johnson Babajide, who spoke extensively on the need to embrace health tech rather than search engines for health information. In his submissions, he noted a huge number of people have been addicted to self-diagnosis by reading health-related internet pictures before seeing physicians which fosters late presentation of health issues. “Self-diagnosis is a wrong thing to do. People who go on search engines for self-diagnosis do not understand what they are reading or know the consequences. Search engines mostly use keywords and some unwanted materials may pop up and the results may inflict fear on the average readers and it’s wrong.
“Some people go as far as checking medications and symptoms on search engines which is worse. One may read about some health issues online but checking for medications is worse. It’s called self-medication.”
Bababjide, however, did not discourage people who read about their health online, but stressed that it should be done after a physician has been consulted and not before.
“The disadvantages of sourcing health information online are more than its advantages. I always advise it’s better to go to the health facility to see a physician and get properly diagnosed than rely on search engines.
“It’s not bad reading more about the health issue after they have seen the physician and not after they have seen the physician.
“I have seen health technology and it has been agreed that most of the health technology still have human beings who are professionals fielding accurate answers to questions asked and backend and answering over a telemedicine platform and also treating data that Artificial Intelligence (AI) uses to generate whatever answers are requested.
“Unlike search engines, AI doesn’t feed itself but on data that would have been treated. I can attest that telemedicine and AI are the future. To every Nigerian who rely on search engines for self-diagnosis, they need to stop that bad habit because anxiety might come into play and may lead to worse health conditions,” he said.
Juxtaposing the accuracy of internet search engines and health technology applications, United Kingdom-based Artificial Intelligence, and Machine Language, Dayo Ojerinde, also concurred with its terrific reading about ailments and medications online.
He said: “While it is entirely not bad for people to read about ailments and learn more about diseases online, it is highly sacrosanct to draw a line between AI-focused diagnostics and search engines.
“Before the advent of artificial intelligence, people relied on Google and other search engines to increase their knowledge of ailments. But with the advent of artificial intelligence, healthcare, and diagnostics have received a boost.
“AI-focused diagnostics and search engines serve different purposes and operate using distinct methodologies. AI diagnostics are designed to analyse specific data inputs (like medical images, symptoms, or sensor data) to provide detailed, context-aware insights, diagnoses, or recommendations.
“With search engines, people can read from the plethora of materials that have been ‘dumped’ on the Internet. The Internet search engine can be used by anyone and that makes it dangerous for people to just go on the Internet and consume all manners of health information.
“Taking into consideration the issues of source, trust, and authority of the authors, some might assume all is well. For instance, people will so much believe what a Professor of Medicine has published than other information published by someone who doesn’t have domain knowledge.”
On data processing, he said “Artificial Intelligence diagnostics use machine learning algorithms and models trained on specialised datasets to interpret complex data patterns. These systems are often fine-tuned for specific applications, such as identifying diseases in medical images or predicting equipment failures in industrial settings.
“The output is typically a diagnosis, risk assessment, or recommendation based on the input data. These systems often provide a high level of specificity and accuracy for their intended applications. “Users input detailed and specific data, and the AI system processes this to provide precise and relevant results. They can operate autonomously, often requiring minimal input once configured. In fields like healthcare, AI diagnostics are subject to strict regulations and standards to ensure safety and efficacy.”
In comprehensive language, Ojerinde explained the purpose of search engines.
“Search engines are designed to help users find information on the internet by indexing web pages and retrieving relevant results based on user queries. They use algorithms to index and rank web pages, considering factors like keywords, relevance, authority, and user engagement metrics. The focus is on broad information retrieval rather than deep analysis of specific data inputs.
“The output is a list of web pages, articles, or other online resources that match the search query. Results are often ranked by relevance and popularity. “Users input search queries, usually in the form of keywords or natural language questions, and the search engine returns a list of potentially relevant web pages. Interaction is typically more general and less specialised compared to AI diagnostics.
“Search engines are less regulated compared to diagnostic systems, though they do follow certain guidelines and laws, especially concerning data privacy and advertising,” he said.
Speaking further on the essential of AI, he said, “AI diagnostics are highly specialised for specific tasks, while search engines are general-purpose tools for finding a wide range of information.
“AI diagnostics work with specific data inputs (like medical images) to provide detailed, context-specific outputs. Search engines work with text-based queries to return a broad range of web resources.
“AI diagnostics are used in specialised fields requiring precise analysis (healthcare, industrial maintenance), while search engines are used for general information retrieval across various topics. “AI diagnostics leverage machine learning models trained on specialised data, whereas search engines use algorithms optimised for indexing and retrieving vast amounts of web content. These differences highlight the distinct roles and functionalities of AI diagnostics and search engines in their respective domains.”
In his conclusion, the expert spoke about the reliability of AI and also as a disease risk detector and proactive intervention.
“Artificial Intelligence processes large-scale patient data, extracting valuable insights that inform decision-making. This data-driven approach enables healthcare providers to make more informed and personalised treatment choices.
“AI facilitates in-depth genomic analysis, identifying genetic markers relevant to diseases. This information allows for the development of targeted therapies, maximising treatment effectiveness while minimising side effects.
“Utilising AI algorithms, healthcare systems can predict disease risk and proactively intervene. This empowers individuals to adopt preventive measures, potentially reducing the incidence of certain conditions.
“AI-powered diagnostic tools improve accuracy and speed in identifying medical conditions. Machine learning algorithms analyse medical images, aiding in early detection and precise diagnosis. “AI optimises resource allocation by predicting patient needs and streamlining workflows. This efficiency ensures better utilisation of healthcare resources, reducing costs and improving overall healthcare delivery.
“The integration of AI in precision healthcare is reshaping how medical care is delivered. From personalised treatments to advanced diagnostics, AI contributes significantly to the improvement of patient outcomes and the overall efficiency of healthcare systems.
“With AI comes apps where people can link up with doctors and experts who have domain knowledge about their ailments and can also serve as a means of getting a second opinion.
“There is also a need to preach caution at this point; the advent of AI should never be an avenue for self-medication or self-treatment. Artificial Intelligence will not replace hospitals and won’t replace doctors, the tool is there to complement the work of experts.
“Artificial Intelligence in healthcare cannot work or function effectively without the inputs of authorities in the field of medicine, doctors, and other experts, it is like a symbiotic relationship,” he said.
