Nandish S
Healthcare data and MedTech specialist in medical imaging
nandish-3459
Bangalore, Karnataka, India
369 connections
Joined May 2026
Summary
Experienced medical imaging researcher and academic with a long tenure at Manipal School of Information Sciences and a PhD in Medical Imaging; has published on multimodal registration, 3D visualization and radiomics. orcid+2
Applied AI and MedTech practitioner in industry, having worked as Specialist at L&T Technology Services (Medical Imaging & AI CoE) and serving as Director for AI & Data Analytics at Visukhi, focusing on building healthcare AI solutions and medtech products. ltts+2
Research focus on practical medical-imaging applications including 3D visualization, radiomics and explainable AI; contributions span conference and journal publications and projects intended to support clinical decision-making. ieee+2
Maintains an academic profile and citation record (Google Scholar) and an ORCID researcher identity, indicating ongoing scholarly activity and collaborations in medical imaging and AI. google+1
Work
Education
Projects
Writing
Differential diagnosis of iron deficiency anemia from aplastic anemia using machine learning and explainable Artificial Intelligence utilizing blood attributes
January 1, 2025A study applying multiple machine learning algorithms and explainable AI tools (SHAP, LIME, Eli5, Qlattice, Anchor) to differentiate iron deficiency anemia from aplastic anemia using blood-test attributes; identifies key features used by XAI models and aims to provide clinically useful decision-support.
Radiomics Features Analysis From Lung Cancer Using CT Images
January 1, 2021Conference publication describing extraction and analysis of radiomics features from lung cancer CT datasets (LIDC-IDRI), feature engineering and exploratory data analysis to support downstream modeling.
3D visualization of brain CT and MRI sequence using VTK
January 1, 2017Work describing 3D visualization methods for CT and MRI using VTK for improved neurosurgical planning, including volume rendering approaches and multimodal visualization considerations.