Papers published by Researchers in Health Care.

| 2024 | | 2023 | 2022 | 2021 | 2020 |

2024

  • Amit Sharma, Ekansh Chauhan, Megha S Uppin, Liza Rajasekhar, C V Jawahar, P K Vinod , Lupus Nephritis Subtype Classification with only Slide Level labels , MIDL 2024
  • Suvadeep Maiti, Shivam Kumar Sharma, Raju S. Bapi, Enhancing Healthcare with Eog: a Novel Approach to Sleep Stage Classification , ICASSP 2024

2023

  • A Garg, VV Venkataramani, UD Priyakumar , Single-lead to multi-lead electrocardiogram reconstruction using a modified attention U-Net framework , IJCNN
  • A.Talasila, A.Karthikeyan, S.Alle, M,Maity, UD Priyakumar, Self-Supervision and weak supervision for accurate and interpretable Chest X-ray Classification Models , IJCNN 2023
  • Shanmukh Alle et al, Covid-19 Risk Stratification & Mortality prediction in hospitalized Indian Patients: harnessing clinical data for publich health benefits , PLOS ONE 2023
  • Akansha Srivastava, P K Vinod , Identification and Characterization of Metabolic Subtypes of Endometrial Cancer using a Systems-Level Approach , IJCNN 2023
  • Pindi Krishna Chandraprasad, Kamalaker Dadi, Bapi Raju , Dynamic functional connectivity analysis in individuals with Autism Spectrum Disorder , IJCNN 2023
  • Keerthi S Shetty, Aswin Jose, Mihir Bani, P K Vinod , Network diffusion-based approach for survival prediction and identification of biomarkers using multi-omics data of papillary renal cell carcinoma , MICCAI 2023
  • Anusha Chaturvedi, Kushal Borkar, U Deva Priyakumar, P.K. Vinod , PREHOST: Host Prediction of coronaviridae family using Machine Learning , MICCAI 2023

2022

  • VV Venkataramani, A Garg, UD Priyakumar , Modified Variable Kernel Length ResNets for Heart Murmur Detection and Clinical Outcome Prediction Using Phonocardiogram Recordings , IEEE, CinC
  • Rami Balasubramanian and Vinod P.K. , Inferring miRNA Sponge modules across major neuropsychiatric disorders , MICCAI 2022
  • Kushal Borkar, Anusha Chaturvedi, Vinod P.K., S Bapi Raju , Ayu -Characterization of Healthy Aging from Neuroimaging Data with Deep Learning and rsfMRI , MICCAI 2022
  • Vamsi Kumar, Likith Reddy, Shivam Kumar Sharma, Kamalakar Dadi, Chiranjeevi Yarra, Bapi S. Raju, Srijithesh Rajendran , mulEEG: A Multi-View Representation Learning on EEG Signals , MICCAI 2022

2021

  • AS Reddy, PK Reddy, A Mondal, UD Priyakumar , A Model of Graph Transactional Coverage Patterns with Applications to Drug Discovery , IEEE
  • Likith Reddy; Vivek Talwar; Shanmukh Alle; Raju. S. Bapi; U. Deva Priyakumar, IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification , IEEE International Conference on Systems, Man, and Cybernetics (SMC),2021
  • Yash Khare, Viraj Bagal, Minesh Mathew, Adithi Devi, U. Deva Priyakumar and C. V. Jawahar, MMBERT: Multimodal BERT Pretraining for Improved Medical VQA , IEEE International Symposium on Biomedical Imaging (ISBI),2021
  • Chauhan R, Vinod PK and Jawahar CV, Exploring genetic-histologic relationships in breast cancer , IEEE International Symposium on Biomedical Imaging (ISBI),2021
  • Ashish Menon, Piyush Singh, P. K. Vinod, C V Jawahar, Interactive Learning for Assisting Whole Slide Image Annotation , Asian Conference on Pattern Recognition (ACPR), 2021
  • S Alle, UD Priyakumar, Linear Prediction Residual for Efficient Diagnosis of Parkinson's Disease from Gait , International Conference on Medical Image Computing and Computer-Assisted Intervention, 2021

2020

  • Y Pathak, S Laghuvarapu, S Mehta, U Priyakumar, Chemically interpretable graph interaction network for prediction of pharmacokinetic properties of drug-like molecules , AAAI Conference on Artificial Intelligence
  • Y Pathak, S Laghuvarapu, S Mehta, U Priyakumar, Chemically interpretable graph interaction network for prediction of pharmacokinetic properties of drug-like molecules , 34th AAAI Conference, NewYork, 2020
  • JR Annam, S Kalyanapu, S Ch, J Somala, SB Raju, Classification of ECG Heartbeat Arrhythmia: A Review , Procedia Computer Science, 171, 2020