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Mashup Score: 7
In recent decades, social scientists have debated declining levels of trust in American institutions. At the same time, many American institutions are coming under scrutiny for their use of artificial intelligence (AI) systems. This paper analyzes the results of a survey experiment over a nationally representative sample to gauge the effect that the use of AI has on the American public’s trust in their social institutions, including government, private corporations, police precincts, and hospitals. We find that artificial intelligence systems were associated with significant trust penalties when used by American police precincts, companies, and hospitals. These penalties were especially strong for American police precincts and, in most cases, were notably stronger than the trust penalties associated with the use of smartphone apps, implicit bias training, machine learning, and mindfulness training. Americans’ trust in institutions tends to be negatively impacted by the use of new tools
Source: ieeexplore.ieee.orgCategories: General Medicine News, General HCPsTweet
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Mashup Score: 6
Social isolation is a serious public health issue that can lead to various mental and physical health problems for individuals and jeopardizes their life’s quality. The issue is more critical for older adults and palliative patients who are already suffering from different diseases and lack some abilities for performing their daily tasks. Additionally, this situation worsens when the COVID-19 pandemic adds forced social isolation to people’s lives worldwide. In this paper, we propose a framework for detecting social isolation in community-based palliative care networks. We look at the problem as an outlier detection in community-based social graphs. Hence, we map the network to an attributed weighted social graph. Consequently, each patient is linked to a set of informal and formal care providers. We define formulae and indices to extract the norm of the society in terms of structural connections and assign a value to each individual based on the quality and quantity of its connections
Source: ieeexplore.ieee.orgCategories: General Medicine News, Hem/OncsTweet
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Mashup Score: 14Transformer-based Automated Segmentation of the Median Nerve in Ultrasound Videos of Wrist-to-Elbow Region - 4 month(s) ago
Segmenting the median nerve is essential for identifying nerve entrapment syndromes, guiding surgical planning and interventions, and furthering understanding of nerve anatomy. This study aims to develop an automated tool that can assist clinicians in localizing and segmenting the median nerve from the wrist, mid-forearm, and elbow in ultrasound videos. This is the first fully automated single deep-learning model for accurate segmentation of the median nerve from the wrist to the elbow in ultrasound videos, along with the computation of the cross-sectional area of the nerve. The visual transformer architecture, which was originally proposed to detect and classify 41 classes in YouTube videos, was modified to predict the median nerve in every frame of ultrasound videos. This is achieved by modifying the bounding box sequence matching block of the visual transformer. The median nerve segmentation is a binary class prediction, and the entire bipartite matching sequence is eliminated, enab
Source: ieeexplore.ieee.orgCategories: General Medicine News, General HCPsTweet
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Mashup Score: 10
Capsule endoscopy is about to become an alternative to traditional colonoscopy. One uses a wireless camera to visualize the gastrointestinal (GI) tract. A 3D model based on image sequences obtained from wireless capsule endoscopy (WCE) can be helpful to diagnose or analyse areas of interests. We have therefore investigated the possibility to provide enhanced viewing for gastroenterologists by reconstructing 3D shapes from WCE images. The study is done on virtual graphics-based models of human GI regions. The shape from shading (SFS) method is applied to colon images and the quality of the reconstructed shapes is compared with ground truth models. WCE images suffer from uneven and dim illumination due to point light source. Therefore, we provide a method based on surface normals from reconstructed 3D models to enhance contrast particularity in images capturing larger depths by changing the illumination from point light to directional light. Images of different resolution are also tested
Source: ieeexplore.ieee.orgCategories: General Medicine News, General HCPsTweet
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Mashup Score: 9Integration of Independent Heat Transfer Mechanisms for Non-Contact Cold Sensation Presentation With Low Residual Heat - 6 month(s) ago
Thermal sensation is crucial to enhancing our comprehension of the world and enhancing our ability to interact with it. Therefore, the development of thermal sensation presentation technologies holds significant potential, providing a novel method of interaction. Traditional technologies often leave residual heat in the system or the skin, affecting subsequent presentations. Our study focuses on presenting thermal sensations with low residual heat, especially cold sensations. To mitigate the impact of residual heat in the presentation system, we opted for a non-contact method, and to address the influence of residual heat on the skin, we present thermal sensations without significantly altering skin temperature. Specifically, we integrated two highly responsive and independent heat transfer mechanisms: convection via cold air and radiation via visible light, providing non-contact thermal stimuli. By rapidly alternating between perceptible decreases and imperceptible increases in temper
Source: ieeexplore.ieee.orgCategories: General Medicine News, NeurologyTweet
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Mashup Score: 6Diagnosis of Coexisting Valvular Heart Diseases Using Image-to-Sequence Translation of Contact Microphone Recordings - 7 month(s) ago
Objective: Development of a contact microphone-driven screening framework for the diagnosis of coexisting valvular heart diseases (VHDs). Methods: A sensitive accelerometer contact microphone (ACM) is employed to capture heart-induced acoustic components on the chest wall. Inspired by the human auditory system, ACM recordings are initially transformed into Mel-frequency cepstral coefficients (MFCCs) and their first and second derivatives, resulting in 3-channel images. An image-to-sequence translation network based on the convolution-meets-transformer (CMT) architecture is then applied to each image to find local and global dependencies in images, and predict a 5-digit binary sequence, where each digit corresponds to the presence of a specific type of VHD. The performance of the proposed framework is evaluated on 58 VHD patients and 52 healthy individuals using a 10-fold leave-subject-out cross-validation (10-LSOCV) approach. Results: Statistical analyses suggest an average sensitivity
Source: ieeexplore.ieee.orgCategories: General Medicine News, Latest HeadlinesTweet
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Mashup Score: 3Predicting Radiologists' Gaze with Computational Saliency Models in Mammogram Reading - 9 month(s) ago
Previous studies have shown that there is a strong correlation between radiologists’ diagnoses and their gaze when reading medical images. The extent to which gaze is attracted by content in a visual scene can be characterised as visual saliency. There is a potential for the use of visual saliency in computer-aided diagnosis in radiology. However, little is known about what methods are effective for diagnostic images, and how these methods could be adapted to address specific applications in diagnostic imaging. In this study, we investigate 20 state-of-the-art saliency models including 10 traditional models and 10 deep learning-based models in predicting radiologists’ visual attention while reading 196 mammograms. We found that deep learning-based models represent the most effective type of methods for predicting radiologists’ gaze in mammogram reading; and that the performance of these saliency models can be significantly improved by transfer learning. In particular, an enhanced model
Source: ieeexplore.ieee.orgCategories: General Medicine News, Latest HeadlinesTweet
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Mashup Score: 0A Portable and a Scalable Multi-Channel Wireless Recording System for Wearable Electromyometrial Imaging - 9 month(s) ago
Electromyometrial imaging (EMMI) technology has emerged as one of the promising technology that can be used for non-invasive pregnancy risk stratification and for preventing complications due to pre-term birth. Current EMMI systems are bulky and require a tethered connection to desktop instrumentation, as a result, the system cannot be used in non-clinical and ambulatory settings. In this paper,…
Source: ieeexplore.ieee.orgCategories: General Medicine News, Latest HeadlinesTweet
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Mashup Score: 2
We report on a naturalistic study investigating the effects of routine driving on cardiovascular activation. We recruited 21 healthy young adults from a broad geographic area in the Southwestern United States. Using the participants’ own smartphones and smartwatches, we monitored for a week both their driving and non-driving activities. Monitoring included the continuous recording of a) heart…
Source: ieeexplore.ieee.orgCategories: General Medicine News, Latest HeadlinesTweet
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Mashup Score: 1
Objective: Modern lifestyles are triggering stress at a disproportionate rate for longer periods of time. Chronic or long-lasting stress can pose a risk to our health. Despite advances in physiological recording methods, mental stress remains challenging to quantify and monitor. Methods: We describe an Internet of Medical Things (IoMT) device with electrocardiogram (ECG) recording features. The…
Source: ieeexplore.ieee.orgCategories: Cardiologists, Latest HeadlinesTweet
Effect of Artificial Intelligence on Social Trust in American Institutions #AI https://t.co/bk4YfRgeCX