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Krishnaraj Chadaga

Showing results (1-10 of 26) with videos related to

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Scientific Reports|July 5, 2025
Explainable artificial intelligence driven insights into smoking prediction using machine learning and clinical parametersS Aishwarya, P C Siddalingaswamy, Krishnaraj Chadaga
Scientific Reports|January 24, 2026
Sickle cell disease detection in low-resource conditions using transfer-learning and contrastive-learning coupled with XAIJay Patel, H Muralikrishna, Krishnaraj Chadaga, et al.
Scientific Reports|April 1, 2026
An explainable artificial intelligence framework for ischemic heart disease prediction using enhanced squirrel search feature selectionD Cenitta, N Arul, R Vijaya Arjunan, et al.
Annals of Medicine|July 12, 2023
Artificial intelligence for diagnosis of mild-moderate COVID-19 using haematological markersKrishnaraj Chadaga, Srikanth Prabhu, Vivekananda Bhat, et al.
Bioengineering (Basel, Switzerland)|April 28, 2023
A Decision Support System for Diagnosis of COVID-19 from Non-COVID-19 Influenza-like Illness Using Explainable Artificial IntelligenceKrishnaraj Chadaga, Srikanth Prabhu, Vivekananda Bhat, et al.
Interdisciplinary Sciences, Computational Life Sciences|February 8, 2022
Clinical and Laboratory Approach to Diagnose COVID-19 Using Machine LearningKrishnaraj Chadaga, Chinmay Chakraborty, Srikanth Prabhu, et al.
SLAS Technology|September 9, 2023
COVID-19 diagnosis using clinical markers and multiple explainable artificial intelligence approaches: A case study from EcuadorKrishnaraj Chadaga, Srikanth Prabhu, Vivekananda Bhat, et al.
Scientific Reports|February 18, 2026
Interpretable machine learning and deep neural networks for ICU admission prediction in paediatric respiratory patientsV Srirama, Roshan Kumar, Krishnaraj Chadaga, et al.
Healthcare Technology Letters|September 18, 2025
A Model of the First Trimester Evaluation of Foetal Movements and Their Outcomes via Explainable Artificial Intelligence: A Multicentric StudyManohar Pavanya, Krishnaraj Chadaga, Vennila J, et al.
Scientific Reports|July 24, 2025
Detection of breast cancer using machine learning and explainable artificial intelligenceTharunya Arravalli, Krishnaraj Chadaga, H Muralikrishna, et al.
Pageof 3

Showing results (1-10 of 26) with videos related to

Sort By:
Pageof 3
Scientific Reports|July 5, 2025
Explainable artificial intelligence driven insights into smoking prediction using machine learning and clinical parametersS Aishwarya, P C Siddalingaswamy, Krishnaraj Chadaga
Scientific Reports|January 24, 2026
Sickle cell disease detection in low-resource conditions using transfer-learning and contrastive-learning coupled with XAIJay Patel, H Muralikrishna, Krishnaraj Chadaga, et al.
Scientific Reports|April 1, 2026
An explainable artificial intelligence framework for ischemic heart disease prediction using enhanced squirrel search feature selectionD Cenitta, N Arul, R Vijaya Arjunan, et al.
Annals of Medicine|July 12, 2023
Artificial intelligence for diagnosis of mild-moderate COVID-19 using haematological markersKrishnaraj Chadaga, Srikanth Prabhu, Vivekananda Bhat, et al.
Bioengineering (Basel, Switzerland)|April 28, 2023
A Decision Support System for Diagnosis of COVID-19 from Non-COVID-19 Influenza-like Illness Using Explainable Artificial IntelligenceKrishnaraj Chadaga, Srikanth Prabhu, Vivekananda Bhat, et al.
Interdisciplinary Sciences, Computational Life Sciences|February 8, 2022
Clinical and Laboratory Approach to Diagnose COVID-19 Using Machine LearningKrishnaraj Chadaga, Chinmay Chakraborty, Srikanth Prabhu, et al.
SLAS Technology|September 9, 2023
COVID-19 diagnosis using clinical markers and multiple explainable artificial intelligence approaches: A case study from EcuadorKrishnaraj Chadaga, Srikanth Prabhu, Vivekananda Bhat, et al.
Scientific Reports|February 18, 2026
Interpretable machine learning and deep neural networks for ICU admission prediction in paediatric respiratory patientsV Srirama, Roshan Kumar, Krishnaraj Chadaga, et al.
Healthcare Technology Letters|September 18, 2025
A Model of the First Trimester Evaluation of Foetal Movements and Their Outcomes via Explainable Artificial Intelligence: A Multicentric StudyManohar Pavanya, Krishnaraj Chadaga, Vennila J, et al.
Scientific Reports|July 24, 2025
Detection of breast cancer using machine learning and explainable artificial intelligenceTharunya Arravalli, Krishnaraj Chadaga, H Muralikrishna, et al.
Pageof 3