Affiliated Research Centers
The following departments across the IIITH community are supporting this initiative and bridging the gap between technology and healthcare.
- Cognitive Sciene Lab(CSL)
- Center for Visual Information Technology(CVIT)
- Centre for Computational Natural Sciences and Bioinformatics(CCNSB)
- Language Technologies Research Center (LTRC)
- Machine Learning Lab, IIIT-Hyderabad
- Center for VLSI and Embedded Systems Technology (CVEST)
- Signal Processing and Communications Research Center (SPCRC)
Focus Areas
Healthcare at IHub-Data aspires to foster a culture of AI research where technology advancements are intertwined with the societal impacts at population scale health and well-being. Here are the highlights on the multidisciplinary focus areas that help people to respond thoughtfully and pursue innovative research, create societally useful problem statements, and develop responsible AI solutions in healthcare.
- DIAG (Cancer Diagnostics)
- PH (Public Health)
- NMH (Neuro & Mental Health)
- D4 (Data Driven Drug Discovery)
Healthcare and Artificial Intelligence (HAI) internship Program
During the academic year 2020-21, Prof. C V Jawahar, Research Dean, IIITH, Prof. Deva Priyakumar U, Academic Head, iHub-Data and Prof. Bapi Raju S, Healthcare Head, iHub-Data and Dr. Vinod P.K, Assistant Professor played a key role in brewing up this major innovative interdisciplinary internship program that mainly focuses on leveraging artificial intelligence to solve some real-world challenges in the general area of healthcare.
HAI recruits' full-time interns across the country every year especially in the month of February and March. HAI provides opportunities to research fellows to work on our projects and get mentored by IIITH academia and industry. Every year a set of bright students are formally selected for the Masters by Research program at IIITH, as proof of their excellence and efficiency.
HAI 1.0 B (2021-2022)
Assessment of neurological disorder with audio-visuals
Multi signal analysis for emotion identification
Automatic sleep stage classification and prediction of stroke recurrence
Classification of AUtism Subtype and it's Exposition
Signal analysis on a low-resource wearable ECG device
Electrocardiography Question Answering
Deciphering XRay Models
AI for predicting pathogen mutation
Detecting Colorectal Cancer using Deep learning
HAI 1.0 A (2020-2021)
DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks
LigGPT: Molecular Generation using a Transformer-Decoder Model
MMBERT: Multimodal BERT Pretraining for Improved Medical VQA
IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification
Weakly supervised method for the classification of Astrocytoma and Oligodendroglioma using Histopathology Images
Deep learning in Nephropathology
Nephro-pathology is a discipline focusing on the diagnostic process of kidney diseases (Lupus nephritis, Diabetic nephropathy, Interstitial nephritis, etc.). This project focus on developing tools that help in the identification and characterization of glomeruli in health and disease. This work will involve segmentation and classification of glomeruli.
Characterization (Prediction) of Healthy Ageing using Deep Learning and rs-fMRI
Viral Host Prediction using Machine Learning
Mutation Prediction of Viruses using genomic/ proteomics
