Background The use of social media for disseminating health care information has become increasingly prevalent, making the expanding role artificial intelligence (AI) and machine learning in this process both significant inevitable. This development raises numerous ethical concerns. study explored AI context on platforms (SMPs). It critically examined these technologies from perspectives fairness, accountability, transparency, ethics (FATE), emphasizing computational methodological...

The forces which affect homelessness are complex and often interactive in nature. Social such as addictions, family breakdown, mental illness compounded by structural lack of available low-cost housing, poor economic conditions, insufficient health services. Together these factors impact levels through their dynamic relations. Historic models, static nature, have only been marginally successful capturing relationships.Fuzzy Logic (FL) fuzzy cognitive maps (FCMs) particularly suited to the...

Calculating the semantic similarity between sentences is a long dealt problem in area of natural language processing. The analysis field has crucial role to play research related text analytics. differs as domain operation differs. In this paper, we present methodology which deals with issue by incorporating and corpus statistics. To calculate words sentences, proposed method follows an edge-based approach using lexical database. can be applied variety domains. been tested on both benchmark...

Manual grading of essays by humans is time-consuming and likely to be susceptible inconsistencies inaccuracies. In recent years, an abundance research has been done automate essay evaluation processes, yet little take into consideration the syntax, semantic coherence sentiments essay's text together. Our proposed system incorporates not just rule-based grammar surface level check but also includes similarity sentences. We propose use Graph-based relationships within content polarity opinion...

Family physicians in Ontario provide most of the primary care to healthcare system. However, given their broad scope practice, they often additional services including emergency medicine, hospital and palliative care. Understanding spectrum provided by family across different regions is important for health human resource planning (HHRP). We investigated Ontario, Canada using a provincial physician database administrative billing data from 2017. Billing codes were used define 18 general that...

This study examines the performance of Large Language Models (LLMs) in Aspect-Based Sentiment Analysis (ABSA), with a focus on implicit aspect extraction novel domain. Using synthetic sports feedback dataset, we evaluate open-weight LLMs' ability to extract aspect-polarity pairs and propose metric facilitate evaluation generative models. Our findings highlight both potential limitations LLMs ABSA task.

Meningitis is characterized by an inflammation of the meninges, or membranes surrounding brain and spinal cord. Early diagnosis treatment crucial for a positive outcome, yet identifying meningitis complex process involving array signs symptoms multiple causal factors which require novel solutions to support clinical decision-making. In this work, we explore potential fuzzy cognitive map assist in modeling meningitis, as tool physicians accurate condition. Fuzzy mapping (FCM) method analysing...

The semantic analysis field has a crucial role to play in the research related text analytics. Calculating similarity between sentences is long-standing problem area of natural language processing, and it differs significantly as domain operation differs. In this paper, we present methodology that can be applied across multiple domains by incorporating corpora-based statistics into standardized algorithm. To calculate words sentences, proposed method follows an edge-based approach using...

Twitter has withstood the test of time as a successful social networking platform. In many circles globally, majority users choose when choosing media outlet for reliable scientific information and news. However, application programming interface (API) limitations do not allow low-cost data science options academia. It becomes very expensive academic researchers to gain full potential analytics available from using free API account. this article, we present our big platform developed at...

When conducting data analysis in the twenty-first century, social media is crucial to due ability provide information on a variety of topics such as health, food, feedback products, and many others. Presently, users utilize share their daily lifestyles. For example, travel locations, exercises, food are common subjects posts. By analyzing collected from users, health general population can be gauged. This become an integral part federal efforts study nation's people large scale. In this...

According to Public Health Agency of Canada, Cardiovascular Disease (CVD) is the leading cause death among adult men and women. Various research works have applied machine learning/data mining algorithms predict CVD, but these methods suffer from a) lack transparency predictive model building, b) capability introduce human wisdom, c) sufficient data. In this paper we provide a novel approach tackle issues design very robust reasonably accurate model. Our based on Structural Equation Modeling...

Automatic sarcasm detection is a growing field in computer science. Short text messages are increasingly used for communication, especially over social media platforms such as Twitter. Due to insufficient or missing context, unidentified these can invert the meaning of statement, leading confusion and communication failures. This paper covers variety current methods detection, including by posting history machine learning models. Additionally, shift towards deep observable, likely due...

Twitter is a well-known microblogging social site where users express their views and opinions in real-time. As result, tweets tend to contain valuable information. With the advancements of deep learning domain natural language processing, extracting meaningful information from has become growing interest among researchers. Applying existing representation models extract does not often produce good results. Moreover, there no for text analysis specific media domain. Hence, this article, we...

Research community has witnessed substantial growth in the detection of mental health issues and their associated reasons from analysis social media. We introduce a new dataset for Causal Analysis Mental Social media posts (CAMS). Our contributions causal are two-fold: interpretation categorization. an annotation schema this task analysis. demonstrate efficacy our on two different datasets: (i) crawling annotating 3155 Reddit (ii) re-annotating publicly available SDCNL 1896 instances...

Abstract Background The collection and examination of social media has become a useful mechanism for studying the mental activity behavior tendencies users. Through analysis collected set Twitter data, model will be developed predicting positively referenced, drug-related tweets. From this, trends correlations can determined. Methods Social data (tweets attributes) were processed using topic pertaining keywords, such as drug slang use-conditions (methods consumption). Potential candidates...

In most cases, the abstracts of articles in medical domain are publicly available. Although these accessible by everyone, they hard to comprehend for a wider audience due complex vocabulary. Thus, simplifying is essential make research general public.This study aims develop deep learning-based text simplification (TS) approach that converts into simpler version while maintaining quality generated text.A TS using reinforcement learning and transformer-based language models was developed....

Data annotation in NLP is a costly and time-consuming task, traditionally handled by human experts who require extensive training to enhance the task-related background knowledge. Besides, labeling social media texts particularly challenging due their brevity, informality, creativity, varying perceptions regarding sociocultural context of world. With emergence GPT models proficiency various tasks, this study aims establish performance baseline for GPT-4 as text annotator. To achieve this, we...