AI-ML Projects

List of  PhD. scholars working in AI-ML domain for their PhD. work in Thakur College of Engineering and Technology:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


 

 

 

 

Mr. Ranganathan Balasubramanian

Head Of Information Services & Business Intelligence at Bhaktivedanta Hospital & Research Centre

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Undergoing Projects in AI-ML Healthcare

TCET has joint venture with Bhaktivedanta Hospital, Miraroad for their AI-ML Healthcare project.

Mr. Swapnil Gaonkar

General Manager Operations at Bhaktivedanta Hospital & Research Centre

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Machine Learning models are generally shown to benefit the most when they are provided supervised data especially in the health care. This would mean pre-identification of patients needing critical health care based interaction with the Hospital system through mobile applications along with the intervention or endorsement of medical professionals on a case to case basis.

 

Thakur College of Engineering and Technology has been regularly collaborating with BhaktiVedanta Hospital & Research Institute through projects,internships to foster critical thinking and problem solving amongst students to explore various directions of learning and predictions as the need for critical health care , some of them being "Rule augmented Semi-supervised learning and subset" selection and "Self-supervised and unsupervised learning".

Currently 40 Students from Information Technology Department, Thakur College of Engineering and Technology are doing internship at BhaktiVedanta Hospital & Research Institute under the guidance of Mr. Ranganathan Balasubramanian who is  Head Of Information Services & Business Intelligence at Bhaktivedanta Hospital & Research Centre and are involved with various projects and applications. With COVID crisis bringing in new challenges these Applications were specifically thought of to deal with the crisis & changing situations in Health Care. 

The data from these system will be applied on Machine Learning and AI algorithms to have predictable outcomes in the following ways:

  • Track the probability of Patients being serviced at Home

  • Improvise the service given at Home by undersigned learning on data

  • Track the sanitization factors at the Hospital

  • Improvise the sanary quotient at the Hospital

  • Enable daily reporting of service quality through performance indicators