A5101658456- Human Pose and Action Recognition
- Diabetic Foot Ulcer Assessment and Management
- Digital Imaging for Blood Diseases
- Advanced Neural Network Applications
- Artificial Intelligence in Healthcare
- Otolaryngology and Infectious Diseases
- Antimicrobial Resistance in Staphylococcus
- Infective Endocarditis Diagnosis and Management
- Artificial Intelligence in Healthcare and Education
- Machine Learning and Data Classification
- Chronic Lymphocytic Leukemia Research
- Epilepsy research and treatment
- Privacy-Preserving Technologies in Data
- HER2/EGFR in Cancer Research
- Monoclonal and Polyclonal Antibodies Research
- Robotics and Sensor-Based Localization
- Multimodal Machine Learning Applications
- Domain Adaptation and Few-Shot Learning
- COVID-19 Digital Contact Tracing
- Diet and metabolism studies
- Machine Learning and Algorithms
Université de Limoges
2023
University of Southern California
2023
Eisai (United States)
2022
Diabetes affects roughly 537 million people in the world, and it is predicted to reach 783 by 2045. Diabetic Foot Ulcer (DFU) a major issue with diabetes that may lead lower limb amputation. The rapid evolution of DFU demands immediate intervention prevent terrible consequences amputation related complications.This research introduces novel approach utilizing deep neural networks machine learning for accurate classification diabetic foot ulcer images. proposed method harnesses cutting-edge...
Diabetes affects roughly 537 million people, and is predicted to reach 783 by 2045. Foot Ulcer (DFU) a major complication associated with diabetes can lead lower limb amputation. The rapid evolution of diabetic foot ulcers (DFUs) necessitates immediate intervention prevent the severe consequences amputation related complications. Continuous meticulous patient monitoring for individuals crucial currently carried out medical practitioners on daily basis. This research article introduces...
Autonomous driving (AD) perception today relies heavily on deep learning based architectures requiring large scale annotated datasets with their associated costs for curation and annotation. The 3D semantic data are useful core tasks such as obstacle detection ego-vehicle localization. We propose a new dataset, Navya Segmentation (Navya3DSeg), diverse label space corresponding to production grade operational domain, including rural, urban, industrial sites universities from 13 countries. It...
Autonomous driving (AD) perception today relies heavily on deep learning based architectures requiring large scale annotated datasets with their associated costs for curation and annotation. The 3D semantic data are useful core tasks such as obstacle detection ego-vehicle localization. We propose a new dataset, Navya Segmentation (Navya3DSeg), diverse label space corresponding to production grade operational domain, including rural, urban, industrial sites universities from 13 countries. It...
It is a known fact that AI models need massive amounts of data for training. In the medical field, are not necessarily available at single site but distributed over several sites. field sharing, particularly among healthcare institutions, to maintain confidentiality sensitive information often restricts comprehensive utilization real-world in machine learning. To address this challenge, our study experiments with an innovative approach using federated learning enable collaborative model...
Inappropriate dental antibiotic prescriptions to prevent infective endocarditis in the United States results ∼$31 million excess costs healthcare system and patients. This includes out-of-pocket ($20.5 million), drug ($2.69 million) adverse event (eg, Clostridioides difficile hypersensitivity) of $5.82 (amoxicillin), $1.99 (clindamycin), $380,849 (cephalexin).
Abstract Background Lecanemab is a humanized IgG1 monoclonal antibody that preferentially targets soluble aggregated Aβ species (protofibrils) with activity at insoluble fibrils. A subcutaneous (SC) formulation in development as an alternative to intravenous (IV) infusion. The present study evaluated the absolute bioavailability (BA), pharmacokinetics (PK), safety and immunogenicity of lecanemab following single fixed 700 mg SC dose. Methods This was open‐label, parallel‐group conducted...
Active Learning (AL) has remained relatively unexplored for LiDAR perception tasks in autonomous driving datasets. In this study we evaluate Bayesian active learning methods applied to the task of dataset distillation or core subset selection (subset with near equivalent performance as full dataset). We also effect application data augmentation (DA) within AL based distillation. perform these experiments on Semantic-KITTI dataset. extend our over existing work only 1/4th same Addition DA and...