AIMC Topic: Humans

Clear Filters Showing 23001 to 23010 of 95995 articles

Combining Metabolomics and Machine Learning to Identify Diagnostic and Prognostic Biomarkers in Patients with Non-Small Cell Lung Cancer Pre- and Post-Radiation Therapy.

Biomolecules
Lung cancer is the leading cause of cancer-related deaths globally, with non-small cell lung cancer (NSCLC) accounting for over 85% of cases and poor prognosis in advanced stages. This study explored shifts in circulating metabolite levels in NSCLC p...

A Deep-Learning-Based CPR Action Standardization Method.

Sensors (Basel, Switzerland)
In emergency situations, ensuring standardized cardiopulmonary resuscitation (CPR) actions is crucial. However, current automated external defibrillators (AEDs) lack methods to determine whether CPR actions are performed correctly, leading to inconsi...

How the Degree of Anthropomorphism of Human-like Robots Affects Users' Perceptual and Emotional Processing: Evidence from an EEG Study.

Sensors (Basel, Switzerland)
Anthropomorphized robots are increasingly integrated into human social life, playing vital roles across various fields. This study aimed to elucidate the neural dynamics underlying users' perceptual and emotional responses to robots with varying leve...

Compressed Deep Learning Models for Wearable Atrial Fibrillation Detection through Attention.

Sensors (Basel, Switzerland)
Deep learning (DL) models have shown promise for the accurate detection of atrial fibrillation (AF) from electrocardiogram/photoplethysmography (ECG/PPG) data, yet deploying these on resource-constrained wearable devices remains challenging. This stu...

A pseudonymized corpus of occupational health narratives for clinical entity recognition in Spanish.

BMC medical informatics and decision making
Despite the high creation cost, annotated corpora are indispensable for robust natural language processing systems. In the clinical field, in addition to annotating medical entities, corpus creators must also remove personally identifiable informatio...

Leveraging shortest dependency paths in low-resource biomedical relation extraction.

BMC medical informatics and decision making
BACKGROUND: Biomedical Relation Extraction (RE) is essential for uncovering complex relationships between biomedical entities within text. However, training RE classifiers is challenging in low-resource biomedical applications with few labeled exampl...

Using natural language processing to facilitate the harmonisation of mental health questionnaires: a validation study using real-world data.

BMC psychiatry
BACKGROUND: Pooling data from different sources will advance mental health research by providing larger sample sizes and allowing cross-study comparisons; however, the heterogeneity in how variables are measured across studies poses a challenge to th...

Machine learning for accurate detection of small airway dysfunction-related respiratory changes: an observational study.

Respiratory research
BACKGROUND: The use of machine learning(ML) methods would improve the diagnosis of small airway dysfunction(SAD) in subjects with chronic respiratory symptoms and preserved pulmonary function(PPF). This paper evaluated the performance of several ML a...

Causes of death in individuals with lifetime major depression: a comprehensive machine learning analysis from a community-based autopsy center.

BMC psychiatry
BACKGROUND: Depression can be associated with increased mortality and morbidity, but no studies have investigated the specific causes of death based on autopsy reports. Autopsy studies can yield valuable and detailed information on pathological ailme...

Healthcare leaders' experiences of implementing artificial intelligence for medical history-taking and triage in Swedish primary care: an interview study.

BMC primary care
BACKGROUND: Artificial intelligence (AI) holds significant promise for enhancing the efficiency and safety of medical history-taking and triage within primary care. However, there remains a dearth of knowledge concerning the practical implementation ...