The Department of Biomedical Engineering conducted a guest lecture on the topic “Application of Artificial Intelligence in Enhancing Engineering” on 15.10.2025. The session was delivered by Dr. Harishchander Anandaram, Assistant Professor, Amrita Vishwa Vidyapeetham, Coimbatore, who shared his insights on the application of artificial intelligence in enhancing engineering practices.
Artificial Intelligence (AI) has emerged as a powerful tool in biomedical engineering, revolutionizing the way healthcare systems diagnose diseases, design medical devices, and deliver patient care. By leveraging machine learning, deep learning, and advanced data analytics, AI enhances accuracy, efficiency, and innovation in biomedical applications.
One of the most impactful contributions of AI in biomedical engineering is in medical diagnosis and imaging. AI-based algorithms can analyze X-rays, MRI scans, CT images, and ultrasound data to detect abnormalities such as tumors, fractures, and organ-related diseases with high precision. Deep learning models can identify patterns that may not be easily recognized by human experts, enabling early detection and faster treatment planning. This has significantly improved diagnostic accuracy and reduced human error.
AI also plays a vital role in personalized medicine and treatment optimization. Biomedical engineers use AI to analyze genetic data, patient history, and clinical records to design personalized treatment plans tailored to individual patients. Machine learning models can predict patient responses to specific drugs, helping clinicians select the most effective therapies while minimizing adverse effects. This approach supports precision healthcare and improves patient outcomes.
In the field of biomedical device development, AI accelerates the design and testing of advanced devices such as prosthetics, implants, wearable sensors, and artificial organs. Intelligent algorithms monitor physiological signals from wearable devices to detect irregularities in real time, enabling continuous health monitoring for patients with chronic conditions. AI-based control systems are also widely used in robotic surgical instruments and rehabilitation devices, enhancing accuracy, safety, and recovery speed.
AI further contributes to drug discovery and bioinformatics by analyzing large biological datasets to identify potential drug candidates and predict molecular interactions. This significantly reduces research time, lowers development costs, and accelerates innovation in pharmaceutical engineering.
Moreover, AI supports predictive analytics in healthcare, enabling hospitals to forecast patient needs, optimize resource utilization, and improve clinical decision-making. AI-driven systems can predict disease outbreaks, patient deterioration, and treatment risks, allowing for proactive and timely medical interventions.
In conclusion, the application of artificial intelligence in biomedical engineering enhances engineering practices by improving diagnostic accuracy, personalizing treatment, advancing medical device development, and supporting efficient healthcare delivery.
