383 research outputs found

    Artificial Intelligence for Caries Detection: Value of Data and Information.

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    If increasing practitioners' diagnostic accuracy, medical artificial intelligence (AI) may lead to better treatment decisions at lower costs, while uncertainty remains around the resulting cost-effectiveness. In the present study, we assessed how enlarging the data set used for training an AI for caries detection on bitewings affects cost-effectiveness and also determined the value of information by reducing the uncertainty around other input parameters (namely, the costs of AI and the population's caries risk profile). We employed a convolutional neural network and trained it on 10%, 25%, 50%, or 100% of a labeled data set containing 29,011 teeth without and 19,760 teeth with caries lesions stemming from bitewing radiographs. We employed an established health economic modeling and analytical framework to quantify cost-effectiveness and value of information. We adopted a mixed public-private payer perspective in German health care; the health outcome was tooth retention years. A Markov model, allowing to follow posterior teeth over the lifetime of an initially 12-y-old individual, and Monte Carlo microsimulations were employed. With an increasing amount of data used to train the AI sensitivity and specificity increased nonlinearly, increasing the data set from 10% to 25% had the largest impact on accuracy and, consequently, cost-effectiveness. In the base-case scenario, AI was more effective (tooth retention for a mean [2.5%-97.5%] 62.8 [59.2-65.5] y) and less costly (378 [284-499] euros) than dentists without AI (60.4 [55.8-64.4] y; 419 [270-593] euros), with considerable uncertainty. The economic value of reducing the uncertainty around AI's accuracy or costs was limited, while information on the population's risk profile was more relevant. When developing dental AI, informed choices about the data set size may be recommended, and research toward individualized application of AI for caries detection seems warranted to optimize cost-effectiveness

    Full Tilt: Universal Constructors for General Shapes with Uniform External Forces

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    We investigate the problem of assembling general shapes and patterns in a model in which particles move based on uniform external forces until they encounter an obstacle. In this model, corresponding particles may bond when adjacent with one another. Succinctly, this model considers a 2D grid of “open” and “blocked” spaces, along with a set of slidable polyominoes placed at open locations on the board. The board may be tilted in any of the 4 cardinal directions, causing all slidable polyominoes to move maximally in the specified direction until blocked. By successively applying a sequence of such tilts, along with allowing different polyominoes to stick when adjacent, tilt sequences provide a method to reconfigure an initial board configuration so as to assemble a collection of previous separate polyominoes into a larger shape. While previous work within this model of assembly has focused on designing a specific board configuration for the assembly of a specific given shape, we propose the problem of designing universal configurations that are capable of constructing a large class of shapes and patterns. For these constructions, we present the notions of weak and strong universality which indicate the presence of “excess” polyominoes after the shape is constructed. In particular, for given integers h, w, we show that there exists a weakly universal configuration with O(hw) 1 × 1 slidable particles that can be reconfigured to build any h × w patterned rectangle. We then expand this result to show that there exists a weakly universal configuration that can build any h × w-bounded size connected shape. Following these results, which require an admittedly relaxed assembly definition, we go on to show the existence of a strongly universal configuration (no excess particles) which can assemble any shape within a previously studied “drop” class, while using quadratically less space than previous results. Finally, we include a study of the complexity of deciding if a particle within a configuration may be relocated to another position, and deciding if a given configuration may be transformed into a second given configuration. We show both problems to be PSPACE-complete even when no particles stick to one another and movable particles are restricted to 1 × 1 tiles and a single 2 × 2 polyomino

    High Smac/DIABLO expression is associated with early local recurrence of cervical cancer

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    <p>Abstract</p> <p>Background</p> <p>In a recent pilot report, we showed that Smac/DIABLO mRNA is expressed <it>de novo </it>in a subset of cervical cancer patients. We have now expanded this study and analyzed Smac/DIABLO expression in the primary lesions in 109 cervical cancer patients.</p> <p>Methods</p> <p>We used immunohistochemistry of formalin-fixed, paraffin-embedded tissue sections to analyze Smac/DIABLO expression in the 109 primary lesions. Seventy-eight samples corresponded to epidermoid cervical cancer and 31 to cervical adenocarcinoma. The median follow up was 46.86 months (range 10–186).</p> <p>Results</p> <p>Smac/DIABLO was expressed in more adenocarcinoma samples than squamous tumours (71% vs 50%; p = 0.037). Among the pathological variables, a positive correlation was found between Smac/DIABLO immunoreactivity and microvascular density, a marker for angiogenesis (p = 0.04). Most importantly, Smac/DIABLO immunoreactivity was associated with a higher rate of local recurrence in squamous cell carcinoma (p = 0.002, log rank test). No association was found between Smac/DIABLO and survival rates.</p> <p>Conclusion</p> <p>Smac/DIABLO expression is a potential marker for local recurrence in cervical squamous cell carcinoma patients.</p

    Disability and the Immigrant Health Paradox: Gender and Timing of Migration

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    Although research has documented better health and longer life expectancy among the foreign-born relative to their U.S.-born counterparts, the U.S. Mexican-origin immigrant population is diverse and the healthy immigrant effect likely varies by key structural and demographic factors such as gender, migration history, and duration in the United States. Using a life course framework, we use data from the Hispanic Established Populations for the Epidemiologic Study of the Elderly (H-EPESE 1993–2013) which includes Mexican-American individuals aged 65 and older to assess the heterogeneity in the immigrant health advantage by age of migration and gender. We find that age of migration is an important delineating factor for disability among both men and women. The healthy immigrant hypothesis is only observable among mid- and late-life migrant men for ADL disability. While among immigrant women, late-life migrants are more likely to have an IADL disability putting them at a health disadvantage. These findings illustrate that Mexican immigrants are not a homogeneous group and migrant health selectivity depends on both gender and when migrants arrived in the United States

    Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device

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    This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and - 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application.Trial registration: ISRCTN - 12246987

    Correction to: Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium (<em>Journal of NeuroEngineering and Rehabilitation</em>, (2023), 20, 1, (78), 10.1186/s12984-023-01198-5)

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    \ua9 The Author(s) 2024.Following publication of the original article [1], the author noticed the errors in Table 1, and in Discussion section. In Table 1 under Metric (Gait sequence detection) column, the algorithms GSDB was updated with wrong description, input, output, language and citation and GSDc with wrong description has been corrected as shown below: (Table presented.) Description of algorithms for each metric: gait sequence detection (GSD), initial contact event detection (ICD), cadence estimation (CAD) and stride length estimation (SL) Metric Name Description Input Output Language References GSDA Based on a frequency-based approach, this algorithm is implemented on the vertical and anterior–posterior acceleration signals. First, these are band pass filtered to keep frequencies between 0.5 and 3 Hz. Next, a convolution of a 2 Hz sinewave (representing a template for a gait cycle) is performed, from which local maxima will be detected to define the regions of gait acc_v: vertical acceleration acc_ap: anterior–posterior acceleration WinS = 3 s; window size for convolution OL = 1.5 s; overlap of windows Activity_thresh = 0.01; Motion threshold Fs: sampling frequency Start: beginning of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector End: termination of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector Matlab\uae Iluz, Gazit [40] GSDB This algorithm, based on a time domain-approach, detects the gait periods based on identified steps. First, the norm of triaxial acceleration signal is low-pass filtered (FIR, fc = 3.2 Hz), then a peak detection procedure using a threshold of 0.1 [g] is applied to identify steps. Consecutive steps, detected using an adaptive step duration threshold are associated to gait sequences acc_norm: norm of the 3D-accelerometer signal Fs: sampling frequency th: peak detection threshold: 0.1 (g) Start: beginning of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector End: termination of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector Matlab\uae Paraschiv-Ionescu, Newman [41] GSDc This algorithm utilizes the same approach as GSDBthe only difference being a different threshold for peak detection of 0.15 [g] acc_norm: norm of the 3D-accelerometer signal Fs: sampling frequency th: peak detection threshold: 0.15 (g) Start: beginning of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector End: termination of N gait sequences [s] relative to the start of a recording or a test/trial. Format: 1 7 N vector Matlab\uae Paraschiv-Ionescu, Newman [41] In Discussion section, the paragraph should read as "Based on our findings collectively, we recommend using GSDB on cohorts with slower gait speeds and substantial gait impairments (e.g., proximal femoral fracture). This may be because this algorithm is based on the acceleration norm (overall accelerometry signal rather than a specific axis/direction (e.g., vertical), hence it is more robust to sensor misalignments that are common in unsupervised real-life settings. Moreover, the use of adaptive threshold, that are derived from the features of a subject’s data and applied to step duration for detection of steps belonging to gait sequences, allows increased robustness of the algorithm to irregular and unstable gait patterns" instead of “Based on our findings collectively, we recommend using GSDB on cohorts with slower gait speeds and substantial gait impairments (e.g., proximal femoral fracture). This may be because this algorithm is based on the acceleration norm (overall accelerometry signal rather than a specific axis/direction (e.g., vertical), hence it is more robust to sensor misalignments that are common in unsupervised real-life settings [41]. Moreover, the use of adaptive thresholds, that are derived from the features of a subject’s data and applied to the amplitude of acceleration norm and to step duration for detection of steps belonging to gait sequences, allows increased robustness of the algorithm to irregular and unstable gait patterns”

    Towards Oxide Electronics:a Roadmap

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    At the end of a rush lasting over half a century, in which CMOS technology has been experiencing a constant and breathtaking increase of device speed and density, Moore's law is approaching the insurmountable barrier given by the ultimate atomic nature of matter. A major challenge for 21st century scientists is finding novel strategies, concepts and materials for replacing silicon-based CMOS semiconductor technologies and guaranteeing a continued and steady technological progress in next decades. Among the materials classes candidate to contribute to this momentous challenge, oxide films and heterostructures are a particularly appealing hunting ground. The vastity, intended in pure chemical terms, of this class of compounds, the complexity of their correlated behaviour, and the wealth of functional properties they display, has already made these systems the subject of choice, worldwide, of a strongly networked, dynamic and interdisciplinary research community. Oxide science and technology has been the target of a wide four-year project, named Towards Oxide-Based Electronics (TO-BE), that has been recently running in Europe and has involved as participants several hundred scientists from 29 EU countries. In this review and perspective paper, published as a final deliverable of the TO-BE Action, the opportunities of oxides as future electronic materials for Information and Communication Technologies ICT and Energy are discussed. The paper is organized as a set of contributions, all selected and ordered as individual building blocks of a wider general scheme. After a brief preface by the editors and an introductory contribution, two sections follow. The first is mainly devoted to providing a perspective on the latest theoretical and experimental methods that are employed to investigate oxides and to produce oxide-based films, heterostructures and devices. In the second, all contributions are dedicated to different specific fields of applications of oxide thin films and heterostructures, in sectors as data storage and computing, optics and plasmonics, magnonics, energy conversion and harvesting, and power electronics
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