Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Deep learning (2)
- Fluorescein angiography (2)
- Polypoidal choroidal vasculopathy (2)
- Screening (2)
- Segmentation (2)
-
- Artificial intelligence (1)
- Artificial intelligibility (1)
- Assessment (1)
- Behavioral predictive analytics (1)
- Cephalometrics (1)
- Climate change (1)
- Cognitive sociology (1)
- Grading (1)
- Growth mindset (1)
- Hazard preparedness (1)
- Health informatics (1)
- Human problem-solving (1)
- Imaging (1)
- Landmark detection (1)
- Lanthanide Nanomaterials (1)
- Laplacian Mesh (1)
- Metacognition (1)
- Natural language processing (NLP) (1)
- Neural networks (1)
- Patent dirichlet allocation (1)
- Practical ritualistic activity (1)
- Quasi-decomposability of complexity (1)
- Rubric (1)
- Self-assessment (1)
- Self-health management (1)
Articles 1 - 8 of 8
Full-Text Articles in Medicine and Health Sciences
Artificial Intelligence And The Situational Rationality Of Diagnosis: Human Problem-Solving And The Artifacts Of Health And Medicine, Michael W. Raphael
Artificial Intelligence And The Situational Rationality Of Diagnosis: Human Problem-Solving And The Artifacts Of Health And Medicine, Michael W. Raphael
Publications and Research
What is the problem-solving capacity of artificial intelligence (AI) for health and medicine? This paper draws out the cognitive sociological context of diagnostic problem-solving for medical sociology regarding the limits of automation for decision-based medical tasks. Specifically, it presents a practical way of evaluating the artificiality of symptoms and signs in medical encounters, with an emphasis on the visualization of the problem-solving process in doctor-patient relationships. In doing so, the paper details the logical differences underlying diagnostic task performance between man and machine problem-solving: its principle of rationality, the priorities of its means of adaptation to abstraction, and the effects …
Toward Informatics-Enabled Preparedness For Natural Hazards To Minimize Health Impacts Of Climate Change, Jimmy Phuong, Naomi O. Riches, Luca Calzoni, Gora Datta, Deborah Duran, Asiyah Yu Lin, Ramesh P. Singh, Anthony E. Solomonides, Noreen Y. Whysel, Ramakanth Kavuluru
Toward Informatics-Enabled Preparedness For Natural Hazards To Minimize Health Impacts Of Climate Change, Jimmy Phuong, Naomi O. Riches, Luca Calzoni, Gora Datta, Deborah Duran, Asiyah Yu Lin, Ramesh P. Singh, Anthony E. Solomonides, Noreen Y. Whysel, Ramakanth Kavuluru
Publications and Research
Natural hazards (NHs) associated with climate change have been increasing in frequency and intensity. These acute events impact humans both directly and through their effects on social and environmental determinants of health. Rather than relying on a fully reactive incident response disposition, it is crucial to ramp up preparedness initiatives for worsening case scenarios. In this perspective, we review the landscape of NH effects for human health and explore the potential of health informatics to address associated challenges, specifically from a preparedness angle. We outline important components in a health informatics agenda for hazard preparedness involving hazard-disease associations, social determinants …
Student Self-Grading Form, Brett Whysel
Student Self-Grading Form, Brett Whysel
Open Educational Resources
This is a word document that students use at the beginning, midpoint, and end of a semester to set relevant goals, measure progress towards goals, and self-grade. It is intended to build motivation, metacognition, and accountability. Instructors may use it on its own or to supplement other assessment tools, and improve the accuracy, validity, and fairness of final grades.
Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Ling, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai
Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Ling, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai
Publications and Research
Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.
Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation …
Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Lin, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai
Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Lin, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai
Publications and Research
Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.
Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation of PCV. …
Biomedical Applications Of Lanthanide Nanomaterials, For Imaging, Sensing And Therapy, Qize Zhang, Stephen O'Brien, Jan Grimm
Biomedical Applications Of Lanthanide Nanomaterials, For Imaging, Sensing And Therapy, Qize Zhang, Stephen O'Brien, Jan Grimm
Publications and Research
The application of nanomaterials made of rare earth elements within biomedical sciences continues to make significant progress. The rare earth elements, also called the lanthanides, play an essential role in modern life through materials and electronics. As we learn more about their utility, function, and underlying physics, we can contemplate extending their applications to biomedicine. This particularly applies to diagnosis and radiation therapy due to their relatively unique features, such as an ultra-wide Stokes shift in the luminescence, variable magnetism and potentially tunable properties, due to the library of lanthanides available and their multivalent oxidation state chemistry. The ability to …
Behavioral Predictive Analytics Towards Personalization For Self-Management – A Use Case On Linking Health-Related Social Needs, Bon Sy, Michael Wassil, Helene Connelly, Alisha Hassan
Behavioral Predictive Analytics Towards Personalization For Self-Management – A Use Case On Linking Health-Related Social Needs, Bon Sy, Michael Wassil, Helene Connelly, Alisha Hassan
Publications and Research
The objective of this research is to investigate the feasibility of applying behavioral predictive analytics to optimize patient engagement in diabetes self-management, and to gain insights on the potential of infusing a chatbot with NLP technology for discovering health-related social needs. In the U.S., less than 25% of patients actively engage in self-health management even though self-health management has been reported to associate with improved health outcomes and reduced healthcare costs. The proposed behavioral predictive analytics relies on manifold clustering to identify subpopulations segmented by behavior readiness characteristics that exhibit non-linear properties. For each subpopulation, an individualized auto-regression model and …
Automatic Cephalometric Landmark Detection On X-Ray Images Using Object Detection, Cheng-Ho King, Yin-Lin Wang, Chia-Ling Tsai
Automatic Cephalometric Landmark Detection On X-Ray Images Using Object Detection, Cheng-Ho King, Yin-Lin Wang, Chia-Ling Tsai
Publications and Research
We propose a new deep convolutional cephalometric landmark detection framework for orthodontic treatment. Our proposed method consists of two major steps: landmark detection using a deep neural network for object detection, and landmark repair to ensure one instance per landmark class. For landmark detection, we modify the loss function of the backbone network YOLOv3 to eliminate the constrains on the bounding box and incorporate attention mechanism to improve the detection accuracy. For landmark repair, a triangle mesh is generated from the average face to eliminate superfluous instances, followed by estimation of missing landmarks from the detected ones using Laplacian Mesh. …