AI In MedTech: Opportunities In Implementation Of Innovative Technology
New-age technologies are revolutionizing industries as we know them. An increasing number of medical devices are leveraging the capabilities of Artificial Intelligence (AI) to support therapeutic and diagnostic applications. Recognized for its great capability of algorithms, the application of AI in MedTech improves patient outcomes and healthcare systems by mimicking human intelligence.
AI in MedTech integrates a subset technology – Machine Learning (ML) that helps medical practitioners to collect, process, analyse and segregate enormous amounts of health-related data. Accumulating and analysing an overwhelming flow of data has become extremely easy and possible due to AI, which was previously inconceivable through manual intervention.
The predictive models and algorithms embedded in AI play a crucial role in diagnosing and managing chronic health conditions like cancer, genome diseases, post-pandemic health abnormalities, and the impact of vaccines on human health. According to market stats, AI use in healthcare is projected to grow from USD 6.9 billion in 2022 to USD 67.4 billion by 2027, recording a 46.2 per cent CAGR.
AI in early cancer diagnosis
Performing any treatment with extreme effectiveness and efficiency requires diagnosing a condition early. Tests like mammograms and pap are widely used to check the signs of cancer or precancerous cells that can form a tumor or turn it into cancer. Experts have developed AI to aid medical tests for screening chronic conditions to catch or treat cancer early before it spreads to the entire body.
Mammograms have helped doctors diagnose cancer for years. However, the integration of AI helps them to understand imaging data with great precision and analyse the data for doctors’ interpretation. This further helps in creating a customized disease management plan for every case. For instance, interpreting pituitary gland images can be difficult for doctors to locate tumorous lesions. Similarly, endocrine cancers that required invasive medical examination can be assisted with non-invasive diagnosis and provide the doctor with relevant and reliable data to analyze the patient’s condition and develop a befitting treatment approach.
AI in early detection of pneumonia
The exacerbating impact of the Covid-19 pandemic took a huge toll on human life. That’s when technology experts emphasized using AI and ML to detect conditions like chest congestion and understand the health of the lungs. Such unique algorithms are used in different medical cases that help doctors with data about an individual’s cough and measure the acoustics. This helps medical practitioners in timely and even early diagnosis of respiratory illnesses, including pneumonia which accounts for 14 per cent of all deaths of children under five years old, killing 7,40,180 children in 2019, as per a WHO report.
The predictive model of AI and ML creates automatic diagnosis of health conditions by recording even the changing sounds during coughing that occurs throughout daily life. This makes the diagnosis of the condition easier while promoting contactless consultation and treatments.
Cost efficiency in diagnosis
Healthcare diagnosis and treatment require an extensive amount of money. This also leads to unnecessary medical expenses that were previously impossible to control by human intervention. With the integration of AI, medical practitioners can record operational efficiencies even in the field of radiology. The vast amount of data facilitates fast scans and accuracy in diagnosis, increasing cost efficiency through early and accurate diagnosis.
Additionally, it eliminates repetitive tasks that result in incorrect diagnoses and treatment decisions. Since AI manages large amounts of data effectively, it can mitigate medical errors and optimize medical practitioners’ time through better clarity on medical conditions and treatment.
Furthermore, hospital facilities struggle with inefficient data management. As a result, doctors and patients cannot access repeated scans which can lead to the cost of medical imaging. Effective data management reduces medical costs, and patients are not hassled to undergo multiple tests.
The potential impact of harnessing AI potential is huge in the present market. Medical companies are connecting with MedTech and AI startups to leverage the power of AI and witness tremendous market growth in the years to come. It is also predicted that AI implementation in the medical segment can result in the development of highly useful diagnostic tools to detect abnormalities in diseases.
