The artificial intelligence (AI) revolution has become a key component of Industry 4.0, with GlobalData forecasts predicting that the AI market will reach sales of $93 billion this year, up 12% from 2022.

In recent years, AI has made significant strides in the medical device market, transforming the way healthcare is delivered. With the ability to analyse vast amounts of data, identify patterns, and make predictions, AI-powered medical devices are enhancing diagnostics, treatment plans, and patient care.

According to Alexandra Murdoch, GlobalData medical analyst: “There are many good uses for AI in the medical device industry, such as data management, remote surgery, diagnostic and procedural assisting, clinical trials, and more.

“AI can also be used in hospitals and other healthcare facilities to provide an efficient experience for patients while also making room to treat more patients daily. Some AI platforms focus on automating and prioritising patient safety, and these platforms can help hospitals better manage their operational costs through tracking wait times, as well as reducing inpatient and emergency department length of stay.”

Saving lives with early action

AI algorithms as tools to analyse patient data are by no means a replacement for diagnosis and treatment from a healthcare professional, but they are invaluable assets when it comes to analysing data sets with increasingly astute accuracy. In fact, research from Imperial College London found that AI could identify cancerous lesions in mammograms with even greater accuracy than radiologists, which could take immense pressure off radiology departments which could then focus on moving forward with treatment.

AI also has the potential to revolutionise personalised medicine by leveraging predictive analytics. By analysing patient data, including electronic health records, genomic information, lifestyle factors, and treatment outcomes, AI algorithms can provide tailored treatment plans. This enables healthcare providers to make informed decisions about the most effective interventions and medication dosages for individual patients, resulting in improved treatment outcomes and reduced adverse events.

AI-assisted surgical robotics

Surgical robots are designed to solve the limitations currently present in minimally invasive surgeries, as well as to improve outcomes in open surgical procedures. Surgeons can now perform complex procedures with greater precision and control, reducing the risk of errors and improving patient outcomes. AI algorithms can analyse real-time surgical data, providing surgeons with valuable insights and recommendations during procedures. Additionally, robotic-assisted surgeries offer benefits such as smaller incisions, reduced pain, and faster recovery times for patients.

AI and remote patient monitoring

AI has facilitated the development of advanced wearable technology and medical devices that can monitor vital signs and collect data on patients’ health in real time. These devices, coupled with AI algorithms, enable remote patient monitoring and early detection of potential health issues. For instance, AI-powered wearable devices can continuously track a patient’s heart rate, blood pressure, and glucose levels, alerting healthcare providers to any abnormalities. This not only enhances patient safety but also reduces hospital readmissions and allows for proactive interventions.

Devices such as continuous glucose monitors (CGM) or oximeters are part of an expanding range of remote monitors and sensors. Advances in AI technology to integrate with medical devices mean that healthcare providers can access more quality data, this puts growing pressure on materials innovators to provide components that can keep up.

Alleima is a one-stop-shop solution provider for ultra-fine medical wire components that have been used for remote patient monitoring devices across the globe. Working with medical device manufacturers from the design stage through to final production, Alleima utilises years of experience in metallurgy and process development to configure a component that is perfectly designed for the application, whether it be for deep brain stimulation, continuous glucose monitoring, or surgical tools.

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