Surveys

Medical Data Pecking: A Context-Aware Approach for Automated Quality Evaluation of Structured Medical Data

Background: The use of Electronic Health Records (EHRs) for epidemiological studies and artificial intelligence (AI) training is increasing rapidly. The reliability of the results depends on the accuracy and completeness of EHR data. However, EHR data often contain significant quality issues, including misrepresentations of subpopulations, biases, and systematic errors, as they are primarily col...

The Illusion of Fairness: Auditing Fairness Interventions with Audit Studies

Artificial intelligence systems, especially those using machine learning, are being deployed in domains from hiring to loan issuance in order to automate these complex decisions. Judging both the effectiveness and fairness of these AI systems, and their human decision making counterpart, is a complex and important topic studied across both computational and social sciences. Within machine learni...

Structure and Smoothness Constrained Dual Networks for MR Bias Field Correction

MR imaging techniques are of great benefit to disease diagnosis. However, due to the limitation of MR devices, significant intensity inhomogeneity o...

Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration

Edge computing enables real-time data processing closer to its source, thus improving the latency and performance of edge-enabled AI applications. H...

Evaluating the Prognostic Value of Kansas City Cardiomyopathy Questionnaire (KCCQ) Scores for 6-Month Readmissions in Southeast Asian Populations With Heart Failure.

BACKGROUND: Heart failure (HF) is a prevalent cause of hospital readmissions. Our study aims to determine the correlation between the Kansas City Card...

Data-driven multi-hazard susceptibility and community perceptions assessment using a mixed-methods approach.

Assessing multi-hazard susceptibility and understanding community insights are important for effective disaster risk management; however, limited rese...

A survey of deep-learning-based radiology report generation using multimodal inputs.

Automatic radiology report generation can alleviate the workload for physicians and minimize regional disparities in medical resources, therefore beco...

Integrating machine learning and reliability analysis: A novel approach to predicting heavy metal removal efficiency using biochar.

Soil contamination with heavy metals (HMs) presents critical environmental and public health risks due to their long-term persistence and tendency to ...

Identifying smart technology and artificial intelligence solutions for human factors and ergonomic challenges in all-hazard response: A survey study.

Emergency responders face significant human factors and ergonomic (HF/E) challenges related to physical, cognitive, emotional, and training demands du...

Uncertainty-Aware Graph Contrastive Fusion Network for multimodal physiological signal emotion recognition.

Graph Neural Networks (GNNs) have been widely adopted to mine topological patterns contained in physiological signals for emotion recognition. However...

Dataset-free weight-initialization on restricted Boltzmann machine.

In feed-forward neural networks, dataset-free weight-initialization methods such as LeCun, Xavier (or Glorot), and He initializations have been develo...

Behavioral biases and Fintech adoption: Investigating the role of financial literacy.

This paper studies the influence of behavioral biases on Fintech adoption. Additionally, the role of financial literacy in adaptation of Fintech servi...

Radiomics-based machine learning in prediction of response to neoadjuvant chemotherapy in osteosarcoma: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Osteosarcoma (OS) is the most common primary bone malignancy, and neoadjuvant chemotherapy (NAC) improves survival rates. However...

PBa-LLM: Privacy- and Bias-aware NLP using Named-Entity Recognition (NER)

The use of Natural Language Processing (NLP) in highstakes AI-based applications has increased significantly in recent years, especially since the e...

What Challenges Do Developers Face When Using Verification-Aware Programming Languages?

Software reliability is critical in ensuring that the digital systems we depend on function correctly. In software development, increasing software ...

Point Cloud Compression and Objective Quality Assessment: A Survey

The rapid growth of 3D point cloud data, driven by applications in autonomous driving, robotics, and immersive environments, has led to criticals de...

GRASP-PsONet: Gradient-based Removal of Spurious Patterns for PsOriasis Severity Classification

Psoriasis (PsO) severity scoring is important for clinical trials but is hindered by inter-rater variability and the burden of in person clinical ev...

HyperSORT: Self-Organising Robust Training with hyper-networks

Medical imaging datasets often contain heterogeneous biases ranging from erroneous labels to inconsistent labeling styles. Such biases can negativel...

Masked Autoencoders that Feel the Heart: Unveiling Simplicity Bias for ECG Analyses

The diagnostic value of electrocardiogram (ECG) lies in its dynamic characteristics, ranging from rhythm fluctuations to subtle waveform deformation...

Leveraging Vision-Language Models to Select Trustworthy Super-Resolution Samples Generated by Diffusion Models

Super-resolution (SR) is an ill-posed inverse problem with many feasible solutions consistent with a given low-resolution image. On one hand, regres...