AIMC Topic: Humans

Clear Filters Showing 9251 to 9260 of 95995 articles

Past, present, and future of exosomes research in cancer: A bibliometric and visualization analysis.

Human vaccines & immunotherapeutics
Cancer seriously threatens the lives and health of people worldwide, and exosomes seem to play an important role in managing cancer effectively, which has attracted extensive attention from researchers in recent years. This study aimed to scientifica...

Enhancing Diagnosis of Psoriasis and Inflammatory Skin Diseases: A Spatially Aligned Multimodal Model Integrating Clinical and Dermoscopic Images.

The Journal of investigative dermatology
Psoriasis is a chronic inflammatory disease with significant physical and psychological impacts. To overcome the limitations of single-modality artificial intelligence models in diagnosing inflammatory skin diseases, we propose a multimodal framework...

SSA-classifier based screening study for Alzheimer's disease.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Alzheimer's is a disease (AD) that affects 10 % of individuals aged ≥ 65, is the most prevalent neurodegenerative disorder. We propose a diagnostic framework integrating plasma attenuated total reflection Fourier transform infrared (ATR-FTIR) spectro...

MGMA-DTI: Drug target interaction prediction using multi-order gated convolution and multi-attention fusion.

Computational biology and chemistry
Accurately predicting drug-target interactions (DTI) is crucial for drug discovery and can reduce drug development costs. Recent deep learning-based DTI predictions have demonstrated promising performance, but they still face two challenges: (i) The ...

Improving radiologists' diagnostic accuracy for lymphovascular invasion in colorectal cancer: insights from a multicenter CT-based study.

Abdominal radiology (New York)
BACKGROUND: The current standard of subjective assessment by radiologists for lymphovascular invasion (LVI) in colorectal cancer (CRC) using CT images often falls short in diagnostic accuracy. This study introduces an advanced CT-based prediction mod...

The pitfalls of fixed-ratio data splitting in radiomics model performance evaluation.

Abdominal radiology (New York)
Over the past decade, radiomics has seen exponential growth, with over ten thousand publications in PubMed and a steady increase in related studies in journals like Abdominal Radiology. Despite the potential of radiomics, a major challenge lies in va...

Incorporating frequency domain features into radiomics for improved prognosis of esophageal cancer.

Medical & biological engineering & computing
Esophageal cancer is a highly aggressive gastrointestinal malignancy with a poor prognosis, making accurate prognostic assessment essential for patient care. The performance of the esophageal cancer prognosis model based on conventional radiomics is ...

Solving two-stage stochastic integer programs via representation learning.

Neural networks : the official journal of the International Neural Network Society
Solving stochastic integer programs (SIPs) is extremely intractable due to the high computational complexity. To solve two-stage SIPs efficiently, we propose a conditional variational autoencoder (CVAE) for scenario representation learning. A graph c...

BC-PMJRS: A Brain Computing-inspired Predefined Multimodal Joint Representation Spaces for enhanced cross-modal learning.

Neural networks : the official journal of the International Neural Network Society
Multimodal learning faces two key challenges: effectively fusing complex information from different modalities, and designing efficient mechanisms for cross-modal interactions. Inspired by neural plasticity and information processing principles in th...

Predicting response to non-invasive brain stimulation in post-stroke upper extremity motor impairment: the importance of neurophysiological and clinical biomarkers.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: Non-invasive brain stimulation (NIBS) is a promising approach to enhance upper extremity motor impairment (UEMI) recovery in post-stroke individuals. However, variability in treatment response poses a significant challenge. Identifying ne...