Applications of deep learning in Alzheimer's disease: A systematic literature review of current trends, methodologies, challenges, innovations, and future directions

S Toumaj, A Heidari, R Shahhosseini… - Artificial Intelligence …, 2024 - Springer
Alzheimer's Disease (AD) constitutes a significant global health issue. In the next 40 years, it
is expected to affect 106 million people. Although more and more people are getting AD …

Crisishatemm: Multimodal analysis of directed and undirected hate speech in text-embedded images from russia-ukraine conflict

A Bhandari, SB Shah, S Thapa… - Proceedings of the …, 2023 - openaccess.thecvf.com
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, and …

Machine learning based algorithms for virtual early detection and screening of neurodegenerative and neurocognitive disorders: a systematic-review

M Yousefi, M Akhbari, Z Mohamadi, S Karami… - Frontiers in …, 2024 - frontiersin.org
Background and aim Neurodegenerative disorders (eg, Alzheimer's, Parkinson's) lead to
neuronal loss; neurocognitive disorders (eg, delirium, dementia) show cognitive decline …

Multi-aspect annotation and analysis of nepali tweets on anti-establishment election discourse

K Rauniyar, S Poudel, S Shiwakoti, S Thapa… - IEEE …, 2023 - ieeexplore.ieee.org
In today's social media-dominated landscape, digital platforms wield substantial influence
over public opinion, particularly during crucial political events such as electoral processes …

Depression screening in humans with AI and deep learning techniques

MA Wani, MA ELAffendi, KA Shakil… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Social media platforms have been widely used as a communication tool where most of the
population expresses their feelings and shares life experiences. Along with general …

Nehate: Large-scale annotated data shedding light on hate speech in nepali local election discourse

S Thapa, K Rauniyar, S Shiwakoti, S Poudel… - ECAI 2023, 2023 - ebooks.iospress.nl
The use of social media during election campaigns has become increasingly popular.
However, the unbridled nature of online discourse can lead to the propagation of hate …

The Role of Natural Language Processing in Detecting Insurance Fraud

VR Saddi, B Gnanapa, S Boddu… - 2023 4th International …, 2023 - ieeexplore.ieee.org
Coverage fraud is an illegal hobby that costs the coverage enterprise billions of bucks yearly
and can be difficult to detect without the proper equipment. One technology that could assist …

A multi-modal dataset for hate speech detection on social media: Case-study of russia-ukraine conflict

S Thapa, A Shah, FA Jafri… - CASE 2022-5th …, 2022 - researchonline.jcu.edu.au
Hate speech consists of types of content (eg text, audio, image) that express derogatory
sentiments and hate against certain people or groups of individuals. The internet …

Speech based detection of Alzheimer's disease: a survey of AI techniques, datasets and challenges

K Ding, M Chetty, A Noori Hoshyar… - Artificial Intelligence …, 2024 - Springer
Alzheimer's disease (AD) is a growing global concern, exacerbated by an aging population
and the high costs associated with traditional detection methods. Recent research has …

Digerati–A multipath parallel hybrid deep learning framework for the identification of mycobacterial PE/PPE proteins

F Li, X Guo, Y Bi, R Jia, ME Pitt, S Pan, S Li… - Computers in Biology …, 2023 - Elsevier
The genome of Mycobacterium tuberculosis contains a relatively high percentage (10%) of
genes that are poorly characterised because of their highly repetitive nature and high GC …