This paper explores the dual role of Large Language Models (LLMs) in context online misinformation and disinformation. In today's digital landscape, where internet social media facilitate rapid dissemination information, discerning between accurate content falsified information presents a formidable challenge. Misinformation, often arising unintentionally, disinformation, crafted deliberately, are at forefront this LLMs such as OpenAI's GPT-4, equipped with advanced language generation...

Alzheimer's disease (AD) is a neurodegenerative disorder resulting in memory loss and cognitive decline caused due to the death of brain cells. It most common form dementia accounts for 60-80% all cases. There no single test diagnosis AD, doctors rely on medical history, neuropsychological assessments, computed tomography (CT) or magnetic resonance imaging (MRI) scan brain, etc. confirm diagnosis. In terms treatment, currently, there neither cure nor any way slow progression AD. However,...

Artificial Intelligence (AI) is considered to be the fourth industrial revolution. with help of big data has transformed all industries around world intelligence refers simulation human or animal in computational systems so that they are programmed think like Intelligent beings and mimic actions intelligent entities. Computational which have can solve different real-world problems far more accurately efficiently than deterministic hardcoded. Since many business analytics cannot solved by...

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), has become an unprecedented public health crisis. To tackle this crisis in effective way different computational solutions involving artificial intelligence and machine learning have been propounded researchers across the world. Artificial Intelligence changed landscape of healthcare industry is being used many corporations governments around world to care issues hence, it finds...

With growing number of ageing population, Parkinson's disease has become a serious problem to huge fraction people above 60. The severely affects the motor system and can lead death patients. There is no cure available for disease. symptoms on seen very late which leads into difficulty in management makes it more difficult when diagnosed later. For early stages disease, there are some medications improve symptoms. certain like slurred speech, problems utterances, etc. earlier. These be...

Text-embedded images are frequently used on social media to convey opinions and emotions, but they can also be a medium for disseminating hate speech, propaganda, extremist ideologies. During the Russia-Ukraine war, both sides text-embedded extensively spread propaganda speech. To aid in moderating such content, this paper introduces CrisisHateMM, novel multimodal dataset of over 4,700 from conflict, annotated non-hate The speech is directed undirected with further individual, community,...

The digitization of healthcare systems has led to the proliferation electronic health records (EHRs), serving as comprehensive repositories patient information. However, vast volume and complexity EHR data present challenges in extracting meaningful insights. This paper addresses need for automated analysis EHRs by proposing a novel graph learning model with label attention (GLLA) temporal event prediction. GLLA utilizes neural networks capture intricate relationships between medical codes...

In the ever-evolving landscape of online discourse and political dialogue, rise hate speech poses a significant challenge to maintaining respectful inclusive digital environment. The context becomes particularly complex when considering Hindi language—a low-resource language with limited available data. To address this pressing concern, we introduce CHUNAV dataset—a collection 11,457 tweets gathered during assembly elections in various states. is purpose-built for categorization...

Surendrabikram Thapa, Aditya Shah, Farhan Jafri, Usman Naseem, Imran Razzak. Proceedings of the 5th Workshop on Challenges and Applications Automated Extraction Socio-political Events from Text (CASE). 2022.

Fine-tuning large pre-trained models for downstream tasks can be really expensive.In the past, researchers have proposed various alternatives like adapter and prompt-based methods tuning these language using minimal parameters.However, applying prompt-tuning smaller has not been effective so far much work is done in pushing forward soft prompting models.To improve training efficiency of reduce size tuned parameters, we propose a novel Adapter-based Efficient Prompt Tuning approach (ADEPT).In...

Study of the ionosphere is important for research in various domains. Especially communication systems, this study holds a great importance. In ionospheric research, there need to delineate useful and non-useful radar returns from ionosphere. The can be used further analysis discarded. When usefulness analyzed by humans, it simply time-consuming prone more human errors. Thus, some machine learning methods are needed returns. algorithms (classical ensemble learners) as well deep models tested...

Alzheimer's Disease (AD) is one of the most common forms neuropsychological disorder in elderly people. It a slow progressive disease affecting brain cells. This affects cognitive abilities people and their daily activities. During course disease, memory gets brutally affected too. Working as well long-term declarative deteriorates AD patients. Due to this deterioration memory, patients tend show decline communicative skills well. reflected speech. usually have poor grammar along with very...

Background: Medical image analysis, particularly in the context of Visual Question Answering (VQA) and captioning, is crucial for accurate diagnosis educational purposes.Objective: Our study introduces BioMedBLIP models, fine-tuned VQA tasks using specialized medical datasets like ROCO MIMIC-CXR, evaluates their performance comparison to state-of-the-art (SOTA) Original BLIP model. Methods:We present nine versions across three downstream various datasets.The models are trained on a varying...

Phishing attacks are one of the most widespread problems over internet. A lot internet users fall into hands attackers every day which accounts millions dollars fraud around globe day. The availability among people who don't have knowledge cyber-attacks adds more to this problem. Thus, there is a need employ intelligent algorithms solve these serious problems. In paper, we present different ways in phishing URLs can be detected using machine learning algorithms. URL based features as well...

The internet has become a common platform for everyone to share their ideas and opinions. user freedom post whatever he/she likes in social networking blogging sites. However, sometimes the content when directed towards certain group of individuals with an intention incite hate or discrimination, causes turmoil society. Such is known as speech. Hate speech can be serious problem peace harmony There are instances where have led unrest extremism. Thus, needs monitored. In this paper, we...