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Found 8 papers, 1 papers with code
Trust in Construction AI-Powered Collaborative Robots: A Qualitative Empirical Analysis
Construction technology researchers and forward-thinking companies are experimenting with collaborative robots (aka cobots), powered by artificial intelligence (AI), to explore various automation scenarios as part of the digital transformation of the industry.
Natural Language Processing in Electronic Health Records in Relation to Healthcare Decision-making: A Systematic Review
Various Machine Learning (ML), Deep Learning (DL) and NLP techniques are studied and compared to understand the limitations and opportunities in this space comprehensively.
Spatial-Temporal Deep Embedding for Vehicle Trajectory Reconstruction from High-Angle Video
In this paper, we developed Spatial-Temporal Deep Embedding (STDE) model that imposes parity constraints at both pixel and instance levels to generate instance-aware embeddings for vehicle stripe segmentation on STMap.
Extracting and Learning Fine-Grained Labels from Chest Radiographs
Chest radiographs are the most common diagnostic exam in emergency rooms and intensive care units today.
Assessment of Amazon Comprehend Medical: Medication Information Extraction
To further establish the generalizability of its medication extraction performance, a set of random internal clinical text notes from NYU Langone Medical Center were also included in this work.
Intracranial Hemorrhage Segmentation Using Deep Convolutional Model
The current clinical protocol to diagnose ICH is examining Computerized Tomography (CT) scans by radiologists to detect ICH and localize its regions.
Wearable-based Mediation State Detection in Individuals with Parkinson's Disease
There is a need to a technology-based system that can provide objective measures about the duration in different medication states that can be used by the treating physician to successfully adjust the therapy.
Geared Rotationally Identical and Invariant Convolutional Neural Network Systems
Theorems and techniques to form different types of transformationally invariant processing and to produce the same output quantitatively based on either transformationally invariant operators or symmetric operations have recently been introduced by the authors.
