A5086520949- Machine Learning in Healthcare
- Artificial Intelligence in Healthcare
- Genetics and Neurodevelopmental Disorders
- Alcohol Consumption and Health Effects
- Advanced Neural Network Applications
- Autism Spectrum Disorder Research
- Healthcare Operations and Scheduling Optimization
- Generative Adversarial Networks and Image Synthesis
- Hepatitis C virus research
- Industrial Vision Systems and Defect Detection
- Functional Brain Connectivity Studies
- Bioinformatics and Genomic Networks
Purdue University West Lafayette
2022-2024
Indiana University
2024
Indiana University School of Medicine
2024
Indiana University – Purdue University Indianapolis
2024
Abstract Objective Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models leverage patients’ longitudinal electronic medical records (EMRs) for personalized precision management of chronic disease progression. Materials Methods We first perform requirement analysis with data scientists determine the visual analytics tasks TrajVis system as well its design functionalities. A graph AI model kidney (CKD)...
Identifying brain abnormalities in autism spectrum disorder (ASD) is critical for early diagnosis and intervention. To explore differences ASD typical development (TD) individuals by detecting structural features using T1-weighted magnetic resonance imaging (MRI), we developed a deep learning-based approach, three-dimensional (3D)-ResNet with inception (I-ResNet), to identify participants TD propose gradient-based backtracking method pinpoint image areas that I-ResNet uses more heavily...
Objective: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models leverage patients' longitudinal electronic medical records (EMR) for personalized precision management of chronic disease progression. Methods: We first perform requirement analysis with data scientists determine the visual analytics tasks TrajVis system as well its design functionalities. A graph AI model kidney (CKD) trajectory inference...
Modern clinical studies collect longitudinal and multimodal data about participants, treatments responses, biospecimens, molecular multiomics data. Such rich complex requires new common models (CDM) to support dissemination research collaboration. We have developed the ARDaC CDM for Alcoholic Hepatitis Network (AlcHepNet) Research Data Commons (ARDaC) translational in national AlcHepNet consortium. The bridges gap between used by electronic capture platform (REDCap) Genomic (GDC) model Gen3...
Product detection in large retail stores requires extensive annotated real data, which is expensive and lacks adaptability when new products are introduced. This paper presents an end-to-end product approach using domain randomization to generate synthetic datasets for training. We propose a set of randomizations at the scene level method generating amounts domain-randomized data. To evaluate performance on this dataset, we pipeline where model pre-trained simulation data fine-tuned small...