AIMC Topic: Humans

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Nonlocal models in biology and life sciences: Sources, developments, and applications.

Physics of life reviews
Mathematical modeling is one of the fundamental techniques for understanding biophysical mechanisms in developmental biology. It helps researchers to analyze complex physiological processes and connect like a bridge between theoretical and experiment...

Deep Ensemble for Central Serous Microscopic Retinopathy Detection in Retinal Optical Coherence Tomographic Images.

Microscopy research and technique
The retina is an important part of the eye that aids in focusing light and visual recognition to the brain. Hence, its damage causes vision loss in the human eye. Central serous retinopathy is a common retinal disorder in which serous detachment occu...

Enhancing atrial fibrillation detection in PPG analysis with sparse labels through contrastive learning.

Computer methods and programs in biomedicine
BACKGROUND: With the advancements in wearable technology, photoplethysmography (PPG) has emerged as a promising technique for detecting atrial fibrillation (AF) due to its ability to capture cardiovascular information. However, current deep learning-...

ScreenDx, an artificial intelligence-based algorithm for the incidental detection of pulmonary fibrosis.

The American journal of the medical sciences
BACKGROUND: Nonspecific symptoms and variability in radiographic reporting patterns contribute to a diagnostic delay of the diagnosis of pulmonary fibrosis. An attractive solution is the use of machine-learning algorithms to screen for radiographic f...

AutoDPS: An unsupervised diffusion model based method for multiple degradation removal in MRI.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Diffusion models have demonstrated their ability in image generation and solving inverse problems like restoration. Unlike most existing deep-learning based image restoration techniques which rely on unpaired or paired data ...

Integrating language into medical visual recognition and reasoning: A survey.

Medical image analysis
Vision-Language Models (VLMs) are regarded as efficient paradigms that build a bridge between visual perception and textual interpretation. For medical visual tasks, they can benefit from expert observation and physician knowledge extracted from text...

TransRM: Weakly supervised learning of translation-enhancing N6-methyladenosine (mA) in circular RNAs.

International journal of biological macromolecules
As our understanding of Circular RNAs (circRNAs) continues to expand, accumulating evidence has demonstrated that circRNAs can interact with microRNAs and RNA-binding proteins to modulate gene expression. More importantly, a subset of circRNAs has be...

Risk factors and an interpretability tool of in-hospital mortality in critically ill patients with acute myocardial infarction.

Clinical medicine (London, England)
OBJECTIVE: We aim to develop and validate an interpretable machine-learning model that can provide critical information for the clinical treatment of critically ill patients with acute myocardial infarction (AMI).

Deep learning-driven prediction in healthcare systems: Applying advanced CNNs for enhanced breast cancer detection.

Computers in biology and medicine
The mortality risk associated with breast cancer is experiencing an exponential rise, underscoring the critical importance of early detection. It is the primary cause of mortality among women under 50 and ranks as the second deadliest disease globall...

Artificial Intelligence user interface preferences in radiology: A scoping review.

Journal of medical imaging and radiation sciences
INTRODUCTION/BACKGROUND: Modern forms of Artificial intelligence (AI) have developed in radiology over the past few years. With the current workforce shortages, in both radiology and radiography professions, AI continues to prove its place in support...