Health
This dataset is in support of my following Research papers
Preprint (Make sure you have read Caution) :
- Novel ß Transtibial Prosthetic 9-DoF Artificial Leg Adaptive Controller - Part I*
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This is two-part open-access webpage of 'Data:B-Bio Models'.This webpage contains datasets of 'Computational Biology'and Novel ß-Bio models, project folders, with clinical and pharmacy investigation in simulation, proposed by me which are Self-Claimed advancements, in support of my Research claims, discoveries, presentations and books. All content can be freely downloaded after sign-up.
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Image : Image was made by me for other International Contest (held by some Medical Institute,USA in the year 2021), 'An intuitive of electromagnetic radiation flowing over epithelial tissue'.
This is an open-access page. All the content can be freely downloaded after sign-up. This webpage contains datasets and models, which are in support of my Research claim/discovery and also used in my Invited/Keynote/Featured/Speaker Presentations.
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Amidst the COVID-19 pandemic, cyberbullying has become an even more serious threat. Our work aims to investigate the viability of an automatic multiclass cyberbullying detection model that is able to classify whether a cyberbully is targeting a victim’s age, ethnicity, gender, religion, or other quality. Previous literature has not yet explored making fine-grained cyberbullying classifications of such magnitude, and existing cyberbullying datasets suffer from quite severe class imbalances.
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This heart disease dataset is curated by combining 3 popular heart disease datasets. The first dataset (Collected from Kaggle) contains 70000 records with 11 independent features which makes it the largest heart disease dataset available so far for research purposes. These data were collected at the moment of medical examination and information given by the patient. Second and third datasets contain 303 and 293 intstances respectively with 13 common features. The three datasets used for its curation are:
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Cardio Data (Kaggle Dataset)
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This heart disease dataset is curated by combining 5 popular heart disease datasets already available independently but not combined before. In this dataset, 5 heart datasets are combined over 11 common features which makes it the largest heart disease dataset available so far for research purposes. The five datasets used for its curation are:
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Shoulder Physiotherapy Activity Recognition 9-Axis Dataset (SPARS9x)
Suggested uses of this dataset include performing supervised classification analysis of physiotherapy exercises, or to perform out-of-distribution detection analysis with unlabeled activities of daily living data.
Description:
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Optical Character Recognition (OCR) system is used to convert the document images, either printed or handwritten, into its electronic counterpart. But dealing with handwritten texts is much more challenging than printed ones due to erratic writing style of the individuals. Problem becomes more severe when the input image is doctor's prescription. Before feeding such image to the OCR engine, the classification of printed and handwritten texts is a necessity as doctor's prescription contains both handwritten and printed texts which are to be processed separately.
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