Results 11 to 20 of about 962,972 (291)
Deep Learning–Based COVID-19 Pneumonia Classification Using Chest CT Images: Model Generalizability
Frontiers in Artificial Intelligence, 2021 Since the outbreak of the COVID-19 pandemic, worldwide research efforts have focused on using artificial intelligence (AI) technologies on various medical data of COVID-19–positive patients in order to identify or classify various aspects of the disease,
Dan Nguyen +9 more
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Predictions of task using neural modeling
Frontiers in Neuroergonomics, 2022 IntroductionA well-designed brain-computer interface (BCI) can make accurate and reliable predictions of a user's state through the passive assessment of their brain activity; in turn, BCI can inform an adaptive system (such as artificial intelligence ...
Elizabeth L. Fox +2 more
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Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, 2023 Background Randomized clinical trials (RCTs) might not be representative of the real‐world population because of unreasonable exclusion criteria. We sought to determine which groups of patients are excluded from RCTs that included lipid‐lowering therapy.
Martina Aeschbacher‐Germann +9 more
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Causal effect on a target population: A sensitivity analysis to handle missing covariates
Journal of Causal Inference, 2022 Randomized controlled trials (RCTs) are often considered the gold standard for estimating causal effect, but they may lack external validity when the population eligible to the RCT is substantially different from the target population.
Colnet Bénédicte +3 more
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Frontiers in Neurology, 2023 ObjectiveThis study aims to assess the value of biomarker based radiomics to predict IDH mutation in gliomas. The patient cohort consists of 160 patients histopathologicaly proven of primary glioma (WHO grades 2–4) from 3 different centers.MethodsTo ...
Georgios S. Ioannidis +11 more
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A Review of Generalizable Transfer Learning in Automatic Emotion Recognition
Frontiers in Computer Science, 2020 Automatic emotion recognition is the process of identifying human emotion from signals such as facial expression, speech, and text. Collecting and labeling such signals is often tedious and many times requires expert knowledge.
Kexin Feng, Theodora Chaspari
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Enhancing precision in human neuroscience
eLife, 2023 Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability – in science in general, but also specifically in human neuroscience – have fueled an extensive ...
Stephan Nebe +24 more
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Retrieval cues fail to influence contextualized evaluations. [PDF]
, 2020 Initial evaluations generalise to new contexts, whereas counter-attitudinal evaluations are context-specific. Counter-attitudinal information may not change evaluations in new contexts because perceivers fail to retrieve counter-attitudinal cue ...
Calanchini, Jimmy +6 more
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Lower-Limb Joint Torque Prediction Using LSTM Neural Networks and Transfer Learning
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022 Estimation of joint torque during movement provides important information in several settings, such as effect of athletes’ training or of a medical intervention, or analysis of the remaining muscle strength in a wearer of an assistive device.
Longbin Zhang +3 more
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Analyzing differences in the costs of treatment across centers within economic evaluations [PDF]
, 2001 Objectives: Assessments of health technologies increasingly include economic evaluations conducted alongside clinical trials. One particular concern with economic evaluations conducted alongside clinical trials is the generalizability of results from one
Coyle, D, Drummond, M F
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