FDA General

(Blind) Users Really Do Heed Aural Telephone Scam Warnings

This paper reports on a study exploring how two groups of individuals, legally blind (n=36) and sighted ones (n=36), react to aural telephone scam warnings in naturalistic settings. As spoofing a CallerID is trivial, communicating the context of an incoming call instead offers a better possibility to warn a receiver about a potential scam. Usually, such warnings are visual in nature and fail to ...

Fan-Beam CT Reconstruction for Unaligned Sparse-View X-ray Baggage Dataset

Computed Tomography (CT) is a technology that reconstructs cross-sectional images using X-ray images taken from multiple directions. In CT, hundreds of X-ray images acquired as the X-ray source and detector rotate around a central axis, are used for precise reconstruction. In security baggage inspection, X-ray imaging is also widely used; however, unlike the rotating systems in medical CT, stati...

"Oh, sh*t! I actually opened the document!": An Empirical Study of the Experiences with Suspicious Emails in Virtual Reality Headsets

This paper reports on a study exploring user experiences with suspicious emails and associated warnings when accessed through virtual reality (VR) h...

AR-Facilitated Safety Inspection and Fall Hazard Detection on Construction Sites

Together with industry experts, we are exploring the potential of head-mounted augmented reality to facilitate safety inspections on high-rise const...

How chromatin interactions shed light on interpreting non-coding genomic variants: opportunities and future direc-tions

Genomic variants, including copy number variants (CNVs) and genome-wide associa-tion study (GWAS) single nucleotide polymorphisms (SNPs), represent ...

High-precision medical speech recognition through synthetic data and semantic correction: UNITED-MEDASR

Automatic Speech Recognition (ASR) systems in the clinical domain face significant challenges, notably the need to recognise specialised medical voc...

BioDSNN: a dual-stream neural network with hybrid biological knowledge integration for multi-gene perturbation response prediction.

Studying the outcomes of genetic perturbation based on single-cell RNA-seq data is crucial for understanding genetic regulation of cells. However, the...

Smoke Screens and Scapegoats: The Reality of General Data Protection Regulation Compliance -- Privacy and Ethics in the Case of Replika AI

Currently artificial intelligence (AI)-enabled chatbots are capturing the hearts and imaginations of the public at large. Chatbots that users can bu...

Exploring the Potentials and Challenges of Using Large Language Models for the Analysis of Transcriptional Regulation of Long Non-coding RNAs

Research on long non-coding RNAs (lncRNAs) has garnered significant attention due to their critical roles in gene regulation and disease mechanisms....

PMI-DT: Leveraging Digital Twins and Machine Learning for Predictive Modeling and Inspection in Manufacturing

Over the years, Digital Twin (DT) has become popular in Advanced Manufacturing (AM) due to its ability to improve production efficiency and quality....

SYNOSIS: Image synthesis pipeline for machine vision in metal surface inspection

The use of machine learning (ML) methods for development of robust and flexible visual inspection system has shown promising. However their performa...

AI, Climate, and Regulation: From Data Centers to the AI Act

We live in a world that is experiencing an unprecedented boom of AI applications that increasingly penetrate and enhance all sectors of private and ...

A Thematic Framework for Analyzing Large-scale Self-reported Social Media Data on Opioid Use Disorder Treatment Using Buprenorphine Product

Background: One of the key FDA-approved medications for Opioid Use Disorder (OUD) is buprenorphine. Despite its popularity, individuals often report...

An Integrated Machine Learning and Deep Learning Framework for Credit Card Approval Prediction

Credit scoring is vital in the financial industry, assessing the risk of lending to credit card applicants. Traditional credit scoring methods face ...

Multi-modal Atmospheric Sensing to Augment Wearable IMU-Based Hand Washing Detection

Hand washing is a crucial part of personal hygiene. Hand washing detection is a relevant topic for wearable sensing with applications in the medical...

Machine Learning Approaches for Defect Detection in a Microwell-based Medical Device

Microfluidic devices offer numerous advantages in medical applications, including the capture of single cells in microwell-based platforms for genom...

Understanding how chromatin folding and enzyme competition affect rugged epigenetic landscapes

Epigenetics plays a key role in cellular differentiation and maintaining cell identity, enabling cells to regulate their genetic activity without al...

External Testing of a Deep Learning Model to Estimate Biologic Age Using Chest Radiographs.

Purpose To assess the prognostic value of a deep learning-based chest radiographic age (hereafter, CXR-Age) model in a large external test cohort of A...

A future role for health applications of large language models depends on regulators enforcing safety standards.

Among the rapid integration of artificial intelligence in clinical settings, large language models (LLMs), such as Generative Pre-trained Transformer-...

Challenges and Proposed Additional Considerations for Medical Device Approval of Large Language Models Beyond Conventional AI.