AIMC Topic: Humans

Clear Filters Showing 24971 to 24980 of 95995 articles

Decoding temporal heterogeneity in NSCLC through machine learning and prognostic model construction.

World journal of surgical oncology
BACKGROUND: Non-small cell lung cancer (NSCLC) is a prevalent and heterogeneous disease with significant genomic variations between the early and advanced stages. The identification of key genes and pathways driving NSCLC tumor progression is critica...

Using machine learning to develop preoperative model for lymph node metastasis in patients with bladder urothelial carcinoma.

BMC cancer
BACKGROUND: Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated wit...

IPF-related new macrophage subpopulations and diagnostic biomarker identification - combine machine learning with single-cell analysis.

Respiratory research
Idiopathic pulmonary fibrosis (IPF) is a chronic disease of unknown etiology that lacks a specific treatment. In IPF, macrophages play a key regulatory role as a major component of the lung immune system, especially during inflammation and fibrosis. ...

Primary care physicians' perceptions of artificial intelligence systems in the care of adolescents' mental health.

BMC primary care
BACKGROUND: Given that mental health problems in adolescence may have lifelong impacts, the role of primary care physicians (PCPs) in identifying and managing these issues is important. Artificial Intelligence (AI) may offer solutions to the current ...

Autism spectrum disorders detection based on multi-task transformer neural network.

BMC neuroscience
Autism Spectrum Disorders (ASD) are neurodevelopmental disorders that cause people difficulties in social interaction and communication. Identifying ASD patients based on resting-state functional magnetic resonance imaging (rs-fMRI) data is a promisi...

ASD-SWNet: a novel shared-weight feature extraction and classification network for autism spectrum disorder diagnosis.

Scientific reports
The traditional diagnostic process for autism spectrum disorder (ASD) is subjective, where early and accurate diagnosis significantly affects treatment outcomes and life quality. Thus, improving ASD diagnostic methods is critical. This paper proposes...

A real-world pharmacovigilance study on cardiovascular adverse events of tisagenlecleucel using machine learning approach.

Scientific reports
Chimeric antigen receptor T-cell (CAR-T) therapies are a paradigm-shifting therapeutic in patients with hematological malignancies. However, some concerns remain that they may cause serious cardiovascular adverse events (AEs), for which data are scar...

Dynamically predicting comprehension difficulties through physiological data and intelligent wearables.

Scientific reports
Comprehending digital content written in natural language online is vital for many aspects of life, including learning, professional tasks, and decision-making. However, facing comprehension difficulties can have negative consequences for learning ou...

A high-quality dataset featuring classified and annotated cervical spine X-ray atlas.

Scientific data
Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image recognition in the medical field, which requires large-scale and high-quality training datasets consisting of raw images and annotated i...

An AS-OCT image dataset for deep learning-enabled segmentation and 3D reconstruction for keratitis.

Scientific data
Infectious keratitis is among the major causes of global blindness. Anterior segment optical coherence tomography (AS-OCT) images allow the characterizing of cross-sectional structures in the cornea with keratitis thus revealing the severity of infla...