AIMC Topic: Humans

Clear Filters Showing 1111 to 1120 of 95995 articles

Diagnostic performance of PET-based artificial intelligence for differentiating Parkinson's disease from normal controls or atypical parkinsonism: a systematic review and meta-analysis.

Journal of neurology
PURPOSE: This study aims to evaluate the diagnostic performance of PET-based artificial intelligence (AI) for differentiating Parkinson's disease (PD) from normal controls (NC) or atypical parkinsonism (AP).

LETM2 regulates mitochondrial function and autophagy in diabetic foot ulcers: implications for oxidative stress and therapeutic targeting.

Functional & integrative genomics
Background A major complication of diabetes, diabetic foot ulcers (DFU), has been linked to mitochondrial dysfunction and oxidative stress. Here, we performed analysis of RNA sequencing data from publicly available databases, including single-cell as...

TGM1 as a novel signature gene in psoriasis identified by integrative bioinformatics and experimental validation.

Molecular medicine reports
Psoriasis is a systemic immune‑mediated skin disease, typically considered to be incurable. Identification of meaningful biomarkers has been a notable challenge in psoriasis prevention and management. The present study aimed to determine the signatur...

RamanMAE: Masked Autoencoders Enable Efficient Molecular Imaging by Learning Biologically Meaningful Spectral Representations.

Analytical chemistry
Traditional histopathological analysis of cells and tissue relies on morphological features from stained biopsy samples, which fail to leverage the wealth of chemical information about the underlying pathological states. Raman spectroscopy, a form of...

A machine-learning model to identify concurrent vascular disease in symptomatic patients with chronic obstructive pulmonary disease.

Annals of medicine
AIM/INTRODUCTION: Chronic obstructive pulmonary disease (COPD) is a complex, heterogeneous syndrome often accompanied by vascular diseases that worsen prognosis and quality of life. This study aimed to develop a machine learning model to identify con...

Interactions between long- and short-term synaptic plasticity transform temporal neural representations into spatial.

Proceedings of the National Academy of Sciences of the United States of America
Information processing in the brain relies on the transmission of spikes through chemical synapses whose efficacies often depend on their recent firing history. While effects of such short-term plasticity on neural information processing have long be...

Deep learning reveals how cells pull, buckle, and navigate fibrous environments.

Proceedings of the National Academy of Sciences of the United States of America
Cells in tissues navigate fibrous environments fundamentally differently than they do on flat substrates, but the establishment of cell forces in physiological fibrous settings remains poorly understood. Although factors such as the stiffness of the ...

Enhancing AI-based diabetic retinopathy diagnosis through universal cross-camera image adaptation.

BMJ open ophthalmology
OBJECTIVE: To evaluate the effectiveness of a deep learning-based style adaptation strategy in improving the diagnostic accuracy and cross-camera generalisability of artificial intelligence (AI) for detecting diabetic retinopathy (DR).

Towards an AI-driven registry for postoperative complications: a proof-of-concept study evaluating the opportunities and challenges of AI models.

BMJ health & care informatics
OBJECTIVES: Postoperative complications (PCs) require substantial resources to manage and are cumbersome to monitor. Artificial intelligence (AI), particularly natural language processing (NLP), offers a potential solution by automating and streamlin...

Continuous wireless sensor monitoring with applied diagnostics: Clinical Sensor Pain Scale and Automated Sensor Pain Scale in the NICU.

BMJ health & care informatics
OBJECTIVES: Inappropriately treated pain can have deleterious outcomes in infants. Current tools rely on intermittent, subjective observation requiring specialised paediatric skills. This study aimed to diagnose infant pain through continuous monitor...