Cerebral Palsy (CP), the most common motor disability in childhood, affects individual´s motor skills, movement, and posture. This results in limited activity and a low social participation. Walking has well-recognized physiological and functional benefits. For this purpose, rehabilitation focused on Robot-Assisted Gait Training (RAGT) has shown to improve their mobility and it is increasingly being used in pediatric neurorehabilitation to complement conventional physical therapy.

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The lack of gold standard methodology for synergy quantification of anticancer drugs warrants the consideration of different synergy metrics to develop efficient Artificial Intelligence-based predictive methods. Furthermore, neglecting combination sensitivity in synergy prediction may lead to biased synergistic combinations that are inefficient in conferring anticancer activity.

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It contains the data of four omic profiles (CNV, mRNA, miRNA, and protein) obtained for BRCA, LGG, and LUAD obtained from the TCGA project. 

In addition, we provide synthetic data for a mixture of isotropic distributions.

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The data provided corresponds to the open-source codes and reference images from a computer interface for real-time gait biofeedback using a Wearable Integrated Sensor System for Data Acquisition.This data is the supplmementary material of the publication I. Sanz-Pena, J. Blanco and J. H. Kim, "Computer Interface for Real-Time Gait Biofeedback Using a Wearable Integrated Sensor System for Data Acquisition," in IEEE Transactions on Human-Machine Systems, https://doi.org/10.1109/THMS.2021.3090738

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Microwave-based breast cancer detection is a growing field that has been investigated as a potential novel method for breast cancer detection. Breast microwave sensing (BMS) systems use low-powered, non-ionizing microwave signals to interrogate the breast tissues. While some BMS systems have been evaluated in clinical trials, many challenges remain before these systems can be used as a viable clinical option, and breast phantoms (breast models) allow for rigorous and controlled experimental investigations.

Instructions: 

The University of Manitoba Breast Microwave Imaging Dataset (UM-BMID) isan open-access dataset available to all researchers. The dataset containsdata from experimental scans of MRI-derived breast phantoms.The dataset itself can be found at https://bit.ly/UM-bmid. The complete documentation for the dataset is also available at this link.

A GitHub page associated with the dataset can be found here: https://github.com/UManitoba-BMS/UM-BMID.The dataset is described in an accepted manuscript:T. Reimer, J. Krenkevich, and S. Pistorius, "An open-access experimentaldataset for breast microwave imaging,", in _2020 European Conference onAntennas and Propagation (EuCAP 2020)_, Copenhagen, Denmark, Mar. 2020,pp. 1-5, doi:10.23919/EuCAP48036.2020.9135659.This GitHub repository (https://github.com/UManitoba-BMS/UM-BMID) contains the code used to produce the resultspresented in that paper and supportive scripts for the UM-BMID dataset.

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The original datasets are NPInter4158 [1], NPInter10412 [2], RPI7317 [3], RPI2241 [4], and RPI369 [4]. Only positive samples of them were used in our work.

We used a different strategy to select more reliable negative samples rather than randomly pairing, which was originally introduced by Zhang et al. in the LPI-CNNCP [5] study.

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This dataset consists of EEG data of 40 epileptic seizure patients (both male and female) of age from 4 to 80 years. The raw data was collected from Allengers VIRGO EEG machine at Medisys Hospitals, Hyderabad, India. The EEG electrodes were placed according to 10 – 20 International standard. The EEG data was recorded from 16 channels (FP2-F4, F4-C4, C4-P4, P4-O2, FP1-F3, F3-C3, C3-P3, P3-O1, FP2-F8, F8-T4, T4-T6, T6-O2, FP1-F7, F7-T3, T3-T5, and T5-O1) at 256 samples per second.

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This dataset is taken from 20 subjects over a duration of 1 hour where experiments were done on the upper body bio-impedance with the following objectives:

a)     Evaluate the effect of externally induced perturbance at the SE interface caused by motion, applied pressure, temperature variation and posture change on bio-impedance measurements.

b)     Evaluate the degree of distortion due to artefact at multiple frequencies (10kHz-100kHz) in the bio-impedance measurements.

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The dataset consists of two classes: COVID-19 cases and Healthy cases 

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Unzip the dataset

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