Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 18,171 to 18,180 of 214,278 articles

An intelligent lung nodule classification model using 3D Trans-DenseUnet++-based lung nodule segmentation.

Scientific reports May 14, 2026
Lung nodule detectionis necessary for lung cancer treatment, which is crucial for treating the patients. However, the current dataset comprises only a limited amount of lung Computed Tomography (CT) images, with a significant imbalance between non-no... read more 

Digital Media Use and Psychosocial Health among Adolescent Boys and Young Men.

Current psychiatry reports May 14, 2026
PURPOSE OF REVIEW: To synthesize recent literature highlighting how and why adolescent boys and young men may face unique media-related psychosocial health risks and potential benefits. RECENT FINDINGS: Adolescent boys and young men appear to demonst... read more 

Identification of Mitochondrial Dysfunction-Related Candidate Biomarkers and Analysis of the Immune Cell Infiltration in Epilepsy.

Molecular neurobiology May 14, 2026
Epilepsy is a severe neurological disorder with complex pathogenesis. Mitochondrial dysfunction (MitD) is increasingly recognized as a key driver of epileptogenesis and seizure generation, contributing to neuronal hyperexcitability and network instab... read more 

CT-based interpretable delta-radiomics model for risk stratification of pulmonary ground-glass nodules: a multicentre study.

Insights into imaging May 14, 2026
OBJECTIVES: To develop and externally validate an interpretable fusion model combining multi-time-point CT radiomics with clinical-semantic features to predict invasiveness of pulmonary ground-glass nodules and support three-tier risk stratification.... read more 

Microfluidic co-culture system for synaptically segregated neural networks to explore astrocyte-driven neural pathology.

Microsystems & nanoengineering May 14, 2026
Investigating astrocyte-neuron communication in the absence of neuron-to-neuron signalling is challenging using traditional culture systems due to the complexity of synaptic networks. To address this, we designed a three-compartment microfluidic co-c... read more 

Metaheuristic optimization of deep CNNs for multi-class diagnosis of cervical cancer and lymphoma.

Scientific reports May 14, 2026
Accurate and early diagnosis of cancer is critical for determining effective treatment strategies and improving patient survival rates. However, automated multi-class cancer detection remains an enormous clinical and computational challenge due to th... read more 

Machine learning using PROFUND components for 30-day readmission prediction in multimorbid patients: a prospective multicentre study.

Scientific reports May 14, 2026
Early hospital readmission in multimorbid patients remains a major clinical challenge. Although risk stratification tools are widely used, predictive performance is often limited. The PROFUND index captures frailty, functional dependence, and social ... read more 

Veterinary fracture diagnosis: a deep learning model for dogs long bone fractures.

Scientific reports May 14, 2026
Bone fractures in dogs are common orthopaedic conditions that require accurate diagnosis and rapid intervention. Traditional radiographic interpretation is often time consuming and is subject to variability, emphasizing the need for automated diagnos... read more 

Deep learning and IoT-based framework for sesame plant identification and weed detection.

Scientific reports May 14, 2026
Automated weed identification in agriculture is a prominent and promising technological intervention as it improves the overall crop productivity and yield. But finding weeds in dense sesame fields is still hard because of occlusion and changes in li... read more 

Application of deep learning based motion posture recognition in sports training.

Scientific reports May 14, 2026
The increasing demand for precise and real-time analysis of athletic movements has driven the adoption of advanced deep-learning techniques in sports training. Traditional methods often rely on manual observation or shallow machine learning models, w... read more 
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