The International Institute of Information Technology, Hyderabad (IIIT-H) and The Indus Entrepreneurs (TiE) have signed a memorandum of understanding (MoU) to promote a deep technology special interest group.
According to media reports, the group will nurture next-gen products and companies in fintech, healthtech, medtech, and agritech.
The TiE deep tech special interest group (SIG) aims to become the catalyst to empower, enable, and provide profiting visibility for enterprises and exposure to global applications and markets.
IIIT Hyderabad will support this programme by offering a strong talent pool of engineers, deep tech knowledge base, technocrats, research, and development capabilities.
The deep tech SIG intends to identify, encourage, and showcase the leading deep tech products and companies to the domestic and global community of customers and investors.
The Professor of Co-innovation at IIIT Hyderabad and the Executive Director of TiE exchanged the MoU in the presence of the IIIT Hyderabad Director and the President of TiE.
The programme will identify about nine of the most innovative deep tech products or companies per group, that have to potential the grow.
They will get access to mentors and accelerator programmes. Their products and services will be showcased at TiE global summits and conferences, giving them access to the investor community. They will also be connected with customers and have access to global markets and TiE angel investor networks.
They will be introduced to over 15, 000 entrepreneurs through TiE’s global network of 61 chapters across 14 countries, the TiE Executive Director said.
IIIT Hyderabad is a higher-education institute that focusses on IT, computer science, electronics, and communication.
Last month, the researchers at IIIT Hyderabad used machine learning for the diagnosis and prognosis of cancer by the microscopic examination of tissue.
According to news reports, the computational models developed by the IIIT can classify subtypes of renal cancer and also predict the survival chances of the patients using digital images.
An expert said that the analysis of histopathological images (of sample tissues) was not something the team had done before. The aim was to see how a computer can interpret these images. Histological images contain markers of disease progression and phenotypic information that can have diagnostic and predictive values.
The study conducted by the researchers revealed that the models achieved over 90% accuracy in determining whether the histopathological images represented a tumour or not. It was 94% accurate in determining its subtypes.
Reports noted that unlike more time-consuming manual microscopic analysis, the machine makes the timely detection and diagnosis of cancer possible.
The model can also make survival predictions based on the shape and nuclei features of the tumour.
Apart from this, when a tissue sample is taken for biopsy, it’s known from where it is taken but the site of origin cannot be ascertained. Researchers have managed to show that there can be different sites of origin in renal cancer.
Reports also stated that the IIIT-H research team has been able to classify 33 different types of cancers using histopathological images from the United States government-funded, Cancer Genome Atlas Project. It now wants to work with Indian cancer data sets.