This dataset contains the images used in the paper "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time". M. E. Morocho Cayamcela and W. Lim, "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time," 2019 International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA, 2019, pp. 100-104.

Instructions: 

The code is written for MATLAB. We used transfer learning using AlexNet and GoogLeNet as convolutional neural network (CNN) backbones.

In MATLAB, replace the directory path with yours. If you want to recognize other classes, just add the images from different classes on labeled folders.

Categories:
410 Views

The dataset comprises raw data to validate methods for reliable data collection. We proposed the data collection methods in a path to assess digital healthcare apps. To validate the methods, we conducted experiments in Amazon Mechanical Turk (MTurk), and then we showed that the methods have a significant meaning based on statistical tests.

Categories:
69 Views

Visual representations are always better than narrations in accordance to children, for better understanding. This is quite advantageous in learning school lessons and it eventually helps in engaging the children and enhancing their imaginative skills.

Instructions: 

File would need to be unzipped for access

Categories:
81 Views

Nowadays technology is being used worldwide to cure deadly diseases. Hepatitis is rapidly spreading in Asia over time. Every 12th Pakistani is suffering from a specific form of hepatitis. In this study, we have explored design and technology solutions for assisting patients of hepatitis and to create awareness among the general public. We have suggested an android app, LiveDliver and a paper-based diary, HepOrganizer to help the patients manage their disease and the general public to acquire awareness.

Instructions: 

File would need to be unzipped for access

Categories:
81 Views

Visual representations are always better than narrations in accordance to children, for better understanding. This is quite advantageous in learning school lessons and it eventually helps in engaging the children and enhancing their imaginative skills. Using natural language processing techniques and along the computer graphics it is possible to bridge the gap between these two individual fields, it will not only eliminate the existing manual labor involved instead it can also give rise to efficient and effective system frameworks that can form a foundation for complex applications.

Categories:
67 Views

When sleep matters for the promotion of heart health, multidisciplinary research is essential. The present dataset is fetched from the National Health And Nutrition Survey (NHANES), with the main consumption of carbohydrates, bedtime and waking hours, and High sensitivity C- Reactive Protein (HSCRP) translating cardiovascular risk. As the outcome variable, HSCRP records from 5,665 participants are available in this dataset for analysis purpose.

Categories:
227 Views

Transcranial Doppler (TCD) echo data was recorded from healthy adults and neurocritical care adult patients. The insonated cerebral vessels were the middle cerebral artery (MCA) and the internal carotid artery (ICA). The ultrasound system used in this study was the Philips CX50.

Instructions: 

There are two code examples included. One is a visualizer for plotting the spectrograms and the other is the actual code for tracing the maximal flow velocity.

  • Use the 'spectrogram_viewer.m' MATLAB script in the 'Spectrogram visualizer' folder to visualize the Doppler spectrograms. In this script, set the variables 'filepath' and 'filename' to point to the TCD data.
  • The full algorithm that computes the spectrogram from the Doppler echo and estimates the maximal flow velocity is found in the folder named 'TCD tracing code'. The main function is 'computeCBFVMain.m'. Note, the variables 'filepath' and 'filename' need to point to the TCD data.

Data acquisition: The transcranial Doppler data were collected from healthy volunteers at Massachusetts Institute of Technology (MIT) and from patients in neurocritical care at Boston Medical Center (BMC). Data collection occurred between 2016 and 2020, was approved by the MIT and BMC Institutional Review Boards, and informed consent was obtained from the subjects directly at MIT or from the patients or their legally authorized representatives at BMC. The data consists of 16 recordings from healthy subjects and 29 recordings neurocritical care patients. 

Published papers

F. Wadehn and T. Heldt, "Adaptive Maximal Blood Flow Velocity Estimation From Transcranial Doppler Echos," in IEEE Journal of Translational Engineering in Health and Medicine, vol. 8, pp. 1-11, 2020, Art no. 1800511, doi: 10.1109/JTEHM.2020.3011562.

R. Jaishankar, A. Fanelli, A. Filippidis, T. Vu, J. Holsapple and T. Heldt, "A Spectral Approach to Model-Based Noninvasive Intracranial Pressure Estimation," in IEEE Journal of Biomedical and Health Informatics, vol. 24, no. 8, pp. 2398-2406, Aug. 2020, doi: 10.1109/JBHI.2019.2961403.

 

 

Categories:
533 Views

In an infectious disease outbreak the identification of pathogen genome sequence variants provides epidemiologists with high-resolution transmission diagnostics that can help cluster patients; identify cohorts of individuals who need testing; and identify new variants that may compromise existing vaccines, therapeutics, and low-resolution detection diagnostics.  The Oxford Nanopore MinION™ is a uniquely portable nucleic acid sequencing device that has been used in limited-resource settings for this purpose, e.g., during the 2014-2016 outbreak of Ebolavirus (EBOV) disease in Africa.  We desc

Instructions: 

Multiple README files are found within the compressed archives in this dataset.  Most files are self-explanatory for biomedical research scientists who are familiar with the analysis of variants in nucleotide sequence data.

Categories:
342 Views

Endoscopy is a widely used clinical procedure for the early detection of cancers in hollow-organs such as oesophagus, stomach, and colon. Computer-assisted methods for accurate and temporally consistent localisation and segmentation of diseased region-of-interests enable precise quantification and mapping of lesions from clinical endoscopy videos which is critical for monitoring and surgical planning. Innovations have the potential to improve current medical practices and refine healthcare systems worldwide.

Last Updated On: 
Wed, 08/12/2020 - 20:53

Nextmed project is a software platform for the segmentation and visualization of medical images. It consist on a series of different automatic segmentation algorithms for different anatomical structures and  a platform for the visualization of the results as 3D models.

This dataset contains the .obj and .nrrd files that correspond to the results of applying our automatic lung segmentation algorithm to the LIDC-IDRI dataset.

This dataset relates to 718 of the 1012 LIDC-IDRI scans.

Instructions: 

The file consists in a folder for each result whith the .obj and .nrrd files generated by the Nextmed algorithms.

Categories:
242 Views

Pages