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Artifacts

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Prompt architecture induces methodological artifacts in large language models.

PloS one
We examine how the seemingly arbitrary way a prompt is posed, which we term "prompt architecture," influences responses provided by large language models (LLMs). Five large-scale, full-factorial experiments performing standard (zero-shot) similarity ...

Integrated convolutional neural network for skin cancer classification with hair and noise restoration.

Turkish journal of medical sciences
BACKGROUND/AIM: Skin lesions are commonly diagnosed and classified using dermoscopic images. There are many artifacts visible in dermoscopic images, including hair strands, noise, bubbles, blood vessels, poor illumination, and moles. These artifacts ...

Baseline Drift Tolerant Signal Encoding for ECG Classification with Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Common artefacts such as baseline drift, rescaling, and noise critically limit the performance of machine learning-based automated ECG analysis and interpretation. This study proposes Derived Peak (DP) encoding, a non-parametric method that generates...

A Deep-Learning Empowered, Real-Time Processing Platform of fNIRS/DOT for Brain Computer Interfaces and Neurofeedback.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Brain-Computer Interfaces (BCI) and Neurofeedback (NFB) approaches, which both rely on real-time monitoring of brain activity, are increasingly being applied in rehabilitation, assistive technology, neurological diseases and behavioral disorders. Fun...

Artefacts of Change: The Disruptive Nature of Humanoid Robots Beyond Classificatory Concerns.

Science and engineering ethics
One characteristic of socially disruptive technologies is that they have the potential to cause uncertainty about the application conditions of a concept i.e., they are conceptually disruptive. Humanoid robots have done just this, as evidenced by dis...

Lag-Net: Lag correction for cone-beam CT via a convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Due to the presence of charge traps in amorphous silicon flat-panel detectors, lag signals are generated in consecutively captured projections. These signals lead to ghosting in projection images and severe lag artifacts in ...

An end-to-end neural network for 4D cardiac CT reconstruction using single-beat scans.

Physics in medicine and biology
Motion artifacts remain a significant challenge in cardiac CT imaging, often impairing the accurate detection and diagnosis of cardiac diseases. These artifacts result from involuntary cardiac motion, and traditional mitigation methods typically rely...

Complex-valued neural networks to speed-up MR thermometry during hyperthermia using Fourier PD and PDUNet.

Scientific reports
Hyperthermia (HT) in combination with radio- and/or chemotherapy has become an accepted cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously heated to temperatures between 39 and 43 °C for 60 min. Temperature monit...

Artifact estimation network for MR images: effectiveness of batch normalization and dropout layers.

BMC medical imaging
BACKGROUND: Magnetic resonance imaging (MRI) is an essential tool for medical diagnosis. However, artifacts may degrade images obtained through MRI, especially owing to patient movement. Existing methods that mitigate the artifact problem are subject...