Read the recent blog Projects at CoEHe
Blood based diagnostics
Our members are committed to develop affordable detection and prognosis using blood. We are developing cognitive computing based methods to identify as well as use markers for detection of disorders using blood samples. In addition, we are trying develop methods to characterise diseases like cancer to guide therapeutics.
Anti-Microbial Resistance
Our members are committed to develop affordable detection and prognosis using blood. We are developing cognitive computing based methods to identify as well as use markers for detection of disorders using blood samples. In addition, we are trying develop methods to characterise diseases like cancer to guide therapeutics.
Genomics
Our members are committed to develop affordable detection and prognosis using blood. We are developing cognitive computing based methods to identify as well as use markers for detection of disorders using blood samples. In addition, we are trying develop methods to characterise diseases like cancer to guide therapeutics.
Public Health
Our members are committed to develop affordable detection and prognosis using blood. We are developing cognitive computing based methods to identify as well as use markers for detection of disorders using blood samples. In addition, we are trying develop methods to characterise diseases like cancer to guide therapeutics.
Handling needs in the training, support of Community Health Workers
Developing interactive training and mentoring session for community health workers in india (ASHAs) using mobile phones and interactive voice response systems for better public healthcare in rural communities
Protein Structure Readouts of Cancer Drivers for Precision Medicine
This study focuses on leveraging protein structure readouts to predict cancer drivers for precision medicine applications. By analysing genetic mutations and their impact on protein structures, researchers aim to identify key drivers of cancer development. This approach holds promise for developing targeted therapies tailored to individual patients, enhancing the efficacy of cancer treatment through precision medicine strategies
ECG-iCOVIDNet: Interpretable AI model to identify changes in the ECG signals of post-COVID subjects
ECG-iCOVIDNet is an AI model that identifies changes in ECG signals of post-COVID patients compared to normal individuals. It provides explainability for both patient and population-level differences, aiding in understanding and managing cardiac complications in post-COVID individuals.
Prognostic Outcome Indicators in Critical Care: Deep Learning Insights
Making and validating indicator for prognostic outcomes in critical care and emergency settings. Using data from large number of ICU-stays of adult patients and deep learning models to make useful insights