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  1. 5801
    por Kochskämper, Dorothee, Lips, Anna
    Publicado 2022
    “…Der vorliegende Beitrag beschäftigt sich anhand der Daten der bundesweiten Studierendenbefragung Stu.diCo II (N = 2527) aus dem Sommersemester 2021 mit der Frage, was von den Studierenden während der vorrangig online stattgefundenen Semester besonders vermisst wurde und was aus Sicht der Studierenden aus den Formaten an der Hochschule in Zukunft beibehalten werden sollte. …”
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    So flexibel wie möglich?!: Visionen für ein Studium (Sozial‑)Pädagogik 2035
  2. 5802
    “…AVAILABILITY AND IMPLEMENTATION: HPiP is released as an open-source code under the MIT license that is freely available on GitHub (https://github.com/BabuLab-UofR/HPiP) as well as on Bioconductor (http://bioconductor.org/packages/devel/bioc/html/HPiP.html). …”
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    HPiP: an R/Bioconductor package for predicting host–pathogen protein–protein interactions from protein sequences using ensemble machine learning approach
  3. 5803
    “…The refgenie Data Manager tool can be installed via the Galaxy ToolShed, with source code managed at https://github.com/BlankenbergLab/galaxy-tools-blankenberg/tree/main/data_managers/data_manager_refgenie_pull and released using an MIT license. Access to existing data is also available through CVMFS, with instructions at https://galaxyproject.org/admin/reference-data-repo/. …”
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    Expanding the Galaxy’s reference data
  4. 5804
    “…In this context, CDs have been successfully grafted into diverse silica nanostructures through various synthesis methods (e.g., solgel chemistry, inverse microemulsion, surfactant templating, and molecular imprinting technology (MIT)), imparting hybrid nanostructures with multimodal properties for distinct objectives. …”
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    A Brief Review of Carbon Dots–Silica Nanoparticles Synthesis and their Potential Use as Biosensing and Theragnostic Applications
  5. 5805
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    Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis
  6. 5806
    “…The EEG signals are obtained from ten patients’ data from the CHB-MIT dataset. Pair-wise electrode spectral coherence is calculated in the full band and five sub-bands of EEG signals. …”
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    Quantitative Analysis of Inter- and Intrahemispheric Coherence on Epileptic Electroencephalography Signal
  7. 5807
    por Nasim, Amnah, Kim, Yoon Sang
    Publicado 2022
    “…Using ECG records from the MIT-BIH, heartbeats are identified to start at 250 ms before and end at 450 ms after the respective R-peak positions. …”
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    DE-PNN: Differential Evolution-Based Feature Optimization with Probabilistic Neural Network for Imbalanced Arrhythmia Classification
  8. 5808
    “…We conducted a secondary data analysis of a Massachusetts Institute of Technology (MIT) survey with Facebook to assess COVID-19 beliefs, behaviours, and norms. …”
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    Consumption of Herbal Supplements or Homeopathic Remedies to Prevent COVID-19 and Intention of Vaccination for COVID-19 in Latin America and the Caribbean
  9. 5809
    “…AVAILABILITY AND IMPLEMENTATION: https://topsyturvy.csail.mit.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.…”
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    Topsy-Turvy: integrating a global view into sequence-based PPI prediction
  10. 5810
    “…Es werden zahlreiche Empfehlungen zum Umgang mit den mutmaßlich von akuter sexualisierter Gewalt bzw. einer Vergewaltigung betroffenen Minderjährigen, zur Erstversorgung, zu Versorgungsformen (z. …”
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    Statement of the DGGG – Recommendations on the Care and Support of Female Minors Suspected of Having Been Subjected to Acute Sexual Violence or Rape
  11. 5811
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    EEG alpha and pupil diameter reflect endogenous auditory attention switching and listening effort
  12. 5812
    “…Some of the healthy and unhealthy datasets have been taken in real-time, augmented, and fused with the Kaggle dataset, i.e., Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH dataset). The CAA-TL worked on the accuracy of heart problem detection by using different methods like ResNet50, AlexNet, and SqueezeNet. …”
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    ECG Classification for Detecting ECG Arrhythmia Empowered with Deep Learning Approaches
  13. 5813
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    SARS-CoV-2-Antigenschnelltests: Zum sicheren Nachweis einer SARS-CoV-2-Infektion nicht geeignet
  14. 5814
    “…We curate a dataset of questions from Massachusetts Institute of Technology (MIT)’s largest mathematics courses (Single Variable and Multivariable Calculus, Differential Equations, Introduction to Probability and Statistics, Linear Algebra, and Mathematics for Computer Science) and Columbia University’s Computational Linear Algebra. …”
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    A neural network solves, explains, and generates university math problems by program synthesis and few-shot learning at human level
  15. 5815
    “…The experiment shows that the model has an average sensitivity of 96.51%, an average AUC of 0.92, and a model size of 15.5 k on 18 patients in the CHB-MIT scalp EEG dataset. Compared with traditional deep learning methods, which require a large number of parameters and computational effort and are demanding in terms of storage space and energy consumption, this method is more suitable for implementation on compact, low-power wearable devices as a standard process for building a generic low-consumption graph network model on similar biomedical signals. …”
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    Efficient graph convolutional networks for seizure prediction using scalp EEG
  16. 5816
    por Griesinger, Frank, Jänicke, Martina
    Publicado 2022
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    Was können Register leisten?: Warum Real World Data zur Versorgungsrealität aus Registern so wichtig sind
  17. 5817
    “…However, there are one or more of the following challenges when using deep learning algorithms: (i) struggles with real-life data, (ii) the time after the training phase also requires high processing power, (iii) they are very computationally expensive, requiring large amounts of memory and computational resources, and it is not easy to transfer them to other problems, (iv) they are hard to describe and are not completely understood (black box), and (v) most of the literature is based on the MIT-BIH or PTB databases, which do not cover most of the crucial arrhythmias. …”
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    Automated Detection of Myocardial Infarction and Heart Conduction Disorders Based on Feature Selection and a Deep Learning Model
  18. 5818
    “…Evaluation results for three patients from the CHB–MIT database, for a 10-min seizure prediction horizon (SPH) and a 20-min seizure occurrence period (SOP), averaged sensitivity of 95.70% and a false prediction rate (FPR) of 0.057/h and for the 5-min prediction horizon and the 25-min seizure occurrence period averaged sensitivity of 98.52% and a false prediction rate of (FPR) of 0.045/h. …”
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    Epilepsy seizure prediction with few-shot learning method
  19. 5819
    “…Towards this goal, we aresharing the information presented at a symposium, “Neuroimaging Indicators of Brain Structure and Function - Closing the Gap Between Research and Clinical Application”, co-hosted by the McCance Center for Brain Health at Mass General Hospital and the MIT HST Neuroimaging Training Program on February 12, 2021. …”
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    How Machine Learning is Powering Neuroimaging to Improve Brain Health
  20. 5820
    “…The web link refers to the videos, posters and further information: https://tropeninstitut.charite.de/forschung/charite_covid_19_projekt_fuer_und_mit_obdachlosen_menschen/ CONCLUSIONS: Exclusion from (digital) information is an increasingly important part of the structural marginalization of homeless people. …”
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    Participatory development of inclusive health communication on COVID-19 with homeless people: Anabell Specht
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