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Latest AI and machine learning research in surveys for healthcare professionals.

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Machine Learning Algorithms for Detecting Mental Stress in College Students

In today's world, stress is a big problem that affects people's health and happiness. More and mor...

Multimodal Sentiment Analysis Based on Causal Reasoning

With the rapid development of multimedia, the shift from unimodal textual sentiment analysis to mu...

MAVias: Mitigate any Visual Bias

Mitigating biases in computer vision models is an essential step towards the trustworthiness of ar...

Estimating the treatment effect over time under general interference through deep learner integrated TMLE

Understanding the effects of quarantine policies in populations with underlying social networks is...

Machine learning algorithms to predict the risk of rupture of intracranial aneurysms: a systematic review

Purpose: Subarachnoid haemorrhage is a potentially fatal consequence of intracranial aneurysm rupt...

Fair Diagnosis: Leveraging Causal Modeling to Mitigate Medical Bias

In medical image analysis, model predictions can be affected by sensitive attributes, such as race...

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Detecting Redundant Health Survey Questions Using Language-agnostic BERT Sentence Embedding (LaBSE)

The goal of this work was to compute the semantic similarity among publicly available health surve...

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey

The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with lar...

Quantifying the Reliability of Predictions in Detection Transformers: Object-Level Calibration and Image-Level Uncertainty

DEtection TRansformer (DETR) has emerged as a promising architecture for object detection, offerin...

EsurvFusion: An evidential multimodal survival fusion model based on Gaussian random fuzzy numbers

Multimodal survival analysis aims to combine heterogeneous data sources (e.g., clinical, imaging, ...

Towards Fair Pay and Equal Work: Imposing View Time Limits in Crowdsourced Image Classification

Crowdsourcing is a common approach to rapidly annotate large volumes of data in machine learning a...

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Can Encrypted Images Still Train Neural Networks? Investigating Image Information and Random Vortex Transformation

Vision is one of the essential sources through which humans acquire information. In this paper, we...

Construction of the UXAR-CT -- a User eXperience Questionnaire for Augmented Reality in Corporate Training

Measuring User Experience (UX) with questionnaires is essential for developing and improving produ...

BACSA: A Bias-Aware Client Selection Algorithm for Privacy-Preserving Federated Learning in Wireless Healthcare Networks

Federated Learning (FL) has emerged as a transformative approach in healthcare, enabling collabora...

Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging.

OBJECTIVE: Artificial intelligence (AI) models trained using medical images for clinical tasks often...

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Nov 2024 38942737
Contextual Representation Anchor Network to Alleviate Selection Bias in Few-Shot Drug Discovery

In the drug discovery process, the low success rate of drug candidate screening often leads to ins...

Validity in Network-Agnostic Byzantine Agreement

In Byzantine Agreement (BA), there is a set of $n$ parties, from which up to $t$ can act byzantine...

Health Misinformation in Social Networks: A Survey of IT Approaches

In this paper, we present a comprehensive survey on the pervasive issue of medical misinformation ...

Local Contrastive Editing of Gender Stereotypes

Stereotypical bias encoded in language models (LMs) poses a threat to safe language technology, ye...

Deoxys: A Causal Inference Engine for Unhealthy Node Mitigation in Large-scale Cloud Infrastructure

The presence of unhealthy nodes in cloud infrastructure signals the potential failure of machines,...

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