Health
Reddit is one of the largest social media websites in the world and it contains valuable data about its users and their perspectives organized into virtual communities or subreddits, based on common areas of interest. Substance use issues are particularly salient within this online community due to the burgeoning substance use (opioid) crisis within the United States among other countries. A particularly important location for understanding user perceptions of opioids is the Philadelphia, Pennsylvania, USA region, due to the prevalence associated with overdose deaths. To collect user sen
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588 Views
A list of the 100 posts from /r/Miscarriage/ and /r/ttcafterloss/ subreddits
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89 Views
This data set includes Covid-19 related Tweet messages written in Turkish that contain at least one of four keywords (Covid, Kovid, Corona, Korona). These keywords are used to express Covid-19 virus in Turkey. Tweets collection was started from 11th March 2020, the first Covid-19 case seen in Turkey.
Currently dataset contain 4,8 million tweets with 6 different attribute of each tweets that were sent from 9 March 2020 until 6 May 2020.
The data file contains comma separated values (CSV). It contains the following information (6 Column) for each tweet in the data file:
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5709 Views
Internet of Things (IoT) make the world easy, with healthcare applications being the most important. In general, IoT is used to interconnect advanced medical resources and provide smart and effective healthcare services to people. Advanced sensors can either be worn or embedded in patients' bodies, so that their health can be monitored remotely. Information collected in this way can be analyzed, collected, and mined to make an early prediction of diseases. Processing algorithms help physicians to personalize treatment and it helps to make healthcare affordable, with better results.
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697 Views
This paper applies AI (artificial intelligence) technology to analyze low-dose HRCT (High-resolution chest radiography) data in an attempt to detect COVID-19 pneumonia symptoms. A new model structure is proposed with segmentation of anatomical structures on DNNs-based (deep learning neural network) methods, relying on an abundance of labeled data for proper training.
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3841 Views
This dataset has been collected in the Patient Recovery Center (a 24-hour, 7-day nurse staffed facility) with medical consultant from the Mobile Healthcare Service of Hamad Medical Corporation.
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1731 Views
The dataset comprises up to two weeks of activity data taken from the ankle and foot of 14 people without amputation and 17 people with lower limb amputation. Walking speed, cadence, and lengths of strides taken at and away from the home were considered in this study. Data collection came from two wearable sensors, one inertial measurement unit (IMU) placed on the top of the prosthetic or non-dominant foot, and one accelerometer placed on the same ankle. Location information was derived from GPS and labeled as ‘home’, ‘away’, or ‘unknown’. The dataset contains raw acce
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1856 Views
Detection results of the CircleNet with all test dataset with 1826 images
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113 Views
FallAllD is a large open dataset of human falls and activities of daily living simulated by 15 participants. FallAllD consists of 26420 files collected using three data-loggers worn on the waist, wrist and neck of the subjects. Motion signals are captured using an accelerometer, gyroscope, magnetometer and barometer with efficient configurations that suit the potential applications e.g. fall detection, fall prevention and human activity recognition.
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11049 Views
Evidence-Based Medicine (EBM) aims to apply the best available evidence gained from scientific methods to clinical decision making. A generally accepted criterion to formulate evidence is to use the PICO framework, where PICO stands for Problem/Population, Intervention, Comparison, and Outcome. Automatic extraction of PICO-related sentences from medical literature is crucial to the success of many EBM applications. In this work, we present our Aceso system, which automatically generates PICO-based evidence summaries from medical literature.
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158 Views