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An auto-segmented multi-time window dual-scale neural network for brain-computer interfaces based on event-related potentials.

Journal of neural engineering
Event-related potentials (ERPs) are cerebral responses to cognitive processes, also referred to as cognitive potentials. Accurately decoding ERPs can help to advance research on brain-computer interfaces (BCIs). The spatial pattern of ERP varies with...

Deep learning-enabled classification of kidney allograft rejection on whole slide histopathologic images.

Frontiers in immunology
BACKGROUND: Diagnosis of kidney transplant rejection currently relies on manual histopathological assessment, which is subjective and susceptible to inter-observer variability, leading to limited reproducibility. We aim to develop a deep learning sys...

Nursing workload: use of artificial intelligence to develop a classifier model.

Revista latino-americana de enfermagem
OBJECTIVE: to describe the development of a predictive nursing workload classifier model, using artificial intelligence.

Using multi-label ensemble CNN classifiers to mitigate labelling inconsistencies in patch-level Gleason grading.

PloS one
This paper presents a novel approach to enhance the accuracy of patch-level Gleason grading in prostate histopathology images, a critical task in the diagnosis and prognosis of prostate cancer. This study shows that the Gleason grading accuracy can b...

The freedom to run: developing an autonomous robot matching the needs of visually impaired citizens to technology opportunities.

Disability and rehabilitation. Assistive technology
Visual impairment poses significant challenges in daily life, especially when navigating unfamiliar environments, resulting in inequalities and reduced quality of life. This study aimed to gain an in-depth understanding of the needs and perspectives...

DNN-BP: a novel framework for cuffless blood pressure measurement from optimal PPG features using deep learning model.

Medical & biological engineering & computing
Continuous blood pressure (BP) provides essential information for monitoring one's health condition. However, BP is currently monitored using uncomfortable cuff-based devices, which does not support continuous BP monitoring. This paper aims to introd...

Artificial intelligence for detection of prostate cancer in biopsies during active surveillance.

BJU international
OBJECTIVES: To evaluate a cancer detecting artificial intelligence (AI) algorithm on serial biopsies in patients with prostate cancer on active surveillance (AS).

Accelerated High-Resolution Deep Learning Reconstruction Turbo Spin Echo MRI of the Knee at 7 T.

Investigative radiology
OBJECTIVES: The aim of this study was to compare the image quality of 7 T turbo spin echo (TSE) knee images acquired with varying factors of parallel-imaging acceleration reconstructed with deep learning (DL)-based and conventional algorithms.

Plasma immune profiling combined with machine learning contributes to diagnosis and prognosis of active pulmonary tuberculosis.

Emerging microbes & infections
Tuberculosis (TB) remains one of the deadliest chronic infectious diseases globally. Early diagnosis not only prevents the spread of TB but also ensures effective treatment. However, the absence of non-sputum-based diagnostic tests often leads to del...