The COVID-19 pandemic propelled the development of many technologies, including the cloud, machine learning (ML) and artificial intelligence (AI). The latter two technologies are frequently paired together, with machine learning algorithms driving artificial intelligence technology.
Statista found that the healthcare AI market totaled approximately $11 billion dollars in 2021 — a metric that’s expected to increase to a whopping $188 billion dollars by the end of the decade in 2030. This prompts business leaders within the healthcare space to wonder precisely how machine learning and AI is being utilized.
AI and Machine Learning Use Cases in Healthcare
The healthcare industry has long been known for its advances both medically and in terms of technology. There is an inherent need for continual advancement and improvement in medical care and treatments. This, in turn, drives technological advances.
Machine learning has gone a long way toward improving medical care in the span of just a couple years. ML has expedited advances in surgery, pharmaceuticals and patient care, with physicians using this technology to diagnose and treat patients faster and with greater accuracy. This is just the tip of the high-tech iceberg. Consider some of these AI and machine learning use cases in healthcare and medicine.
Customized Treatments and Medications – Machine learning provides healthcare professionals with the ability to develop personalized medications and custom treatments for a variety of diseases and conditions, including cancer. This has led to dramatic improvements in patient outcomes.
Public Health and Pandemic Predictions – The COVID-19 pandemic shone a spotlight on the topic of pandemic predictions. Machine learning is the ideal technology for processing the large volumes of data that are required to make accurate predictions. Predictions about the spread of an illness — and whether it may reach the level of a regional or global pandemic — give public health officials the ability to take action sooner. They’re also empowered to act in a manner that’s more likely to lead to a positive outcome when they have the ability to make data-driven decisions.
Pharmaceutical Development With AI and ML – The pharmaceutical industry can benefit greatly from machine learning and artificial intelligence, especially when it comes to the development of pharmaceuticals. Data drives the creation and testing process for new drugs and treatment regimens. As such, there’s a clear benefit to leveraging ML and AI in a manner that allows you to process large volumes of data at a rapid clip, identifying patterns and trends that guide the drug development and trials process.
Reducing Errors When Dispensing Pharmaceuticals – There is the matter of human error which can arise as a pharmacist dispenses prescription drugs. It’s estimated that as many as 9,000 Americans die annually in cases involving human error and prescription drugs. Something as simple as a typo on the prescription bottle label or dispensing the wrong milligram size can be disastrous. Machine learning and AI can be leveraged to identify problematic practices and / or processes. Once an issue is identified, a solution can be deployed using AI and process automation to minimize human error and increase accuracy.
Clinical Trials and Research – Advances in the medical field are driven by clinical trials and research. Machine learning-driven AI technology can go a long way toward empowering researchers to make sense of large volumes of data with the identification of trends and patterns. AI can be used to refine the medication or treatment that’s at the center of a clinical trial or research study.
Early Disease Detection – Machine learning and AI can be extremely effective at pinpointing trends and patterns, which is exactly what needs to happen if you’re seeking an early diagnosis. Early symptoms may otherwise be ignored or misattributed. With machine learning technology, you can identify those early signs of a problem, improving outcomes for patients who are living with a vast array of diseases and conditions.
Machine learning and artificial intelligence is also being used in some more traditional ways, such as fraud detection. According to the National Health Care Anti-Fraud Association (NHCAA), healthcare fraud is estimated at as much as $300 billion dollars annually. ML and AI is often used to pinpoint anomalous events and transactions that may be indicative of fraud. This allows for early intervention, minimizing losses.
Finding the Ideal Healthcare AI Development Partner
The right technology — packaged within an engaging, user-friendly software platform — holds the power to be a true game changer, with tools and technology that drive ROI for organizations in the healthcare industry. The team at 7T has experience working with multimodal machine learning-powered AI applications across several industries including the medical and healthcare industry. By working with a top Dallas Digital Transformation development company that’s experienced in the newest emerging technologies like machine learning-powered AI, you’ll maximize your chances of success with quantifiable KPI metrics and ROI.
The Digital Transformation development team here at 7T is guided by the approach of “Digital Transformation Driven by Business Strategy.” As such, the 7T development team works with company leaders who are seeking to solve problems and drive ROI through Digital Transformation and innovative business solutions such as multimodal machine learning-powered AI implementations in the healthcare space.
7T has offices in Dallas, Houston and Austin, but our clientele spans the globe. If you’re ready to learn more about machine learning and AI development solutions for the healthcare field, contact 7T today.