As a true visionary and a machine learning expert, Ketan’s original contribution was to devise a statistical simulation model using deep learning algorithms which identify velocity patterns from hidden, missing, or partial data and recognize objects from various angles. The significance of this advanced model is its ability to determine the severity of cardiac arrest based on the patient’s age, ejection fraction of the heart, and patient follow-up time at the hospital. The model also continuously assesses the infant’s heart block abnormalities and determines the severity based on symptomatic information.

Despite the availability of numerous technologies, it is challenging to diagnose cardiac problems and use investigative procedures accurately. The technological field has already benefited much from Ketan’s study. For instance, he developed a multivariate risk model using advanced neural networks. He included a Feed-Forward Backpropagation neural network, which provided the first evidence of forecasting cardiac arrest in its early stages and impending occurrence. To recognize patterns, the machine learning model analyzes image pixels and groups them into appropriate classes. Natural language processing techniques are incorporated into this AI-driven model to help doctors voice-command the algorithm using raw or real-time unstructured data. According to Ketan, after the data has been organized and analyzed, the model proposes the best courses of action for doctors to take in the event of cardiac arrest immediately.

Numerous researchers, medical professionals, and business leaders believe that relatively few scientists know dynamic digital imaging that uses multivariate classification modeling to find missing patterns and ejection fractions. They claim that this finding has great promise and has the potential to significantly cut treatment costs while increasing cardiac patients’ chances of survival.

With a strong academic pursuit, Ketan is PMP certified by PMI. He holds an undergraduate degree in pharmaceutical sciences (India), MBA/PGDM in international business (India), M.S. in Supply Chain (USA), and M.S. (Honors) in Information Technology (USA). He is pursuing his Ph.D. in Information Technology from the USA. Demonstrating his versatility and technical prowess, Ketan is an IEEE senior member and possesses several renowned publications and awards.

Ketan is a driven research scientist who constantly aspires to greatness and works to use artificial intelligence and machine learning technology in the healthcare industry to improve social and community welfare.