AI Offers Alternatives to Genetic Testing to Make Disease Detection More Accessible.

With the introduction of a myriad of new technologies and innovations based on machine learning, including self-piloted cars, facial recognition, and virtual assistants, artificial intelligence (AI) is rapidly becoming an integral part of our world.

AI’s potential benefits are far-reaching and impact numerous industries with some of the most transformative changes taking place in the healthcare realm. As an increasingly vital healthcare tool, AI is revolutionizing tech-driven medical screening solutions in the area of intelligent disease diagnostics.

A key benefit to AI is its ability to correlate, infer and classify information across very large knowledge and repositories, as well as “noisy” data sets, and often with greater accuracy than human doctors, which could enable clinicians to leverage the technology for screening, diagnostics and clinical decision support.
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Cancer in the pancreas, lungs, and ovaries is difficult to recognize and treat early due to the delay in patient symptoms. By analyzing health data from multiple sources, including health records, wearable devices, medical test results, or medical imaging, machine learning algorithms can match biomarkers to known diseases.

In a January 2023 article published by the National Library of Medicine, researchers concluded, “AI-based algorithms are an effective tool for identifying undiagnosed or less-diagnosed patients … and rare diseases. Thus, AI models for disease diagnosis provide ample opportunity for early diagnosis of patients.”

AI, machine learning and deep learning algorithms open new doors for prevention, early detection, and more effective treatment by identifying physical characteristics associated with various illnesses. When diseases are diagnosed at an earlier stage, healthcare providers can quickly intervene with treatment to slow and even stop the advancement of progressive diseases like cancer and greatly improve patient treatment outcomes.

For decades, genetic testing has been used to diagnose or assess the risk of developing a disease in the future based on an individual’s DNA. One widely used genetic test can detect harmful mutations in BRCA1 and BRCA2 genes in women to identify their risk for multiple different cancers, including breast and ovarian. However, genetic testing has several drawbacks, and now AI technology can be used to determine the likelihood that a patient has a specific disease more quickly and at a lower cost than typical diagnostic tests.

Many conventional diagnostic and genetic tests are expensive and many people forego genetic testing to avoid potential costs and miss a timely, life-saving diagnosis. With new technological innovations, providers can detect diseases cost-effectively by using AI to analyze a patient’s medical history and identify disease-related anomalies. This technology can be implemented affordably worldwide, making disease identification an option for previously unreached demographics.

In addition to the high costs associated with current genetic testing, analysis of a DNA test can take weeks or months to turn around, depending on whether the tested gene is a common one and has an easily recognizable mutation. Although some results may be delivered in a few days, genetic testing still requires multiple specialists and technical staff to assess the findings in the DNA. But AI-driven diagnostic testing timelines significantly outperform genetic testing, using algorithms to process data in real time and obtain results in seconds without the need for highly trained clinicians.

Another key benefit to leveraging AI for disease detection is that it may provide a more comprehensive view of a person’s overall health. Beyond an individual’s genetic profile, several factors contribute to health including medical care and history, personal behaviors, social aspects, and environmental influences. While genetic testing doesn’t evaluate the full scope of a person’s health, AI can incorporate multiple elements or identify the risk for a disease.

By providing clinicians with a deeper understanding of the nuances of their patients’ complete health, the opportunity for AI to help doctors in precision medicine is promising. Several credible tech companies are working to build AI that will create care plans tailored to an individual’s needs based on their diagnosis. As this capacity grows, the hope is that future AI tech will apply machine learning to accurately diagnose and treat diverse maladies while seamlessly integrating into clinical workflows and patient care plans.

As a pioneer in the use of AI to improve health-related outcomes, Luventix is harnessing AI to launch a new technology to help diagnose a multitude of medical conditions by analyzing a single urine sample. This sample can easily be collected at home for little cost but contains vital molecular information that indicates changes in a person’s metabolic profile that are linked to certain diseases. Using gas chromatography, a well-established method for separating chemical compounds, a urine sample is converted into a data-rich, real-time profile of a person’s metabolism that can be used to determine the likelihood that they have a disease. This method captures all the advantages of AI-driven diagnostics with its potential to rapidly deliver comprehensive results to global populations at lower costs.

One of the most exciting benefits of AI is the ability to bring rapid, inexpensive disease detection to global populations. Through remote patient monitoring and an established and widely used model, health data can be automatically and continuously gathered, stored, and transmitted to providers. Now, this clinical data can be processed through AI algorithms that evaluate and classify information relevant to disease detection, bringing medical care and diagnostics to patients who might not receive it otherwise. This includes patients without reliable transportation to a clinic, people who live in rural areas, and underserved communities around the world.

The use of AI is increasing life-changing access to care for these demographics by identifying diseases remotely and reducing the need for physical visits to a clinical provider. However, as in all aspects of healthcare, the privacy of personal information is of utmost importance. As these AI-based models become more integrated into standard practices of care, the existing regulatory frameworks must evolve to ensure both access and continuous improvement of results while maintaining privacy and preventing algorithmic bias.

As healthcare has evolved and new technologies have appeared, industry stakeholders have continually overcome similar challenges to expand medical care to a broader range of people. The potential benefits of AI-driven healthcare are tremendous, and the opportunities for rapid, more accessible diagnostic results at lower costs are transforming the industry in new, unparalleled ways.